Russ Tedrake: Underactuated Robotics, Control, Dynamics and Touch | Lex Fridman Podcast #114
the following is a conversation with russ tedrick a roboticist and professor at mit and vice president of robotics research at toyota research institute or tri he works on control of robots in interesting complicated underactuated stochastic difficult to model situations he's a great teacher and a great person one of my favorites at mit we'll get into a lot of topics in this conversation from his time leading mit's delta robotics challenge team to the awesome fact that he often runs close to a marathon a day to and from work barefoot for a world-class roboticist interested in elegant efficient control of underactually dynamical systems like the human body this fact makes russ one of the most fascinating people i know quick summary of the ads three sponsors magic spoon cereal better help and expressvpn please consider supporting this podcast by going to magicspoon.com lex and using code lex at checkout going to betterhelp.com lex and signing up at expressvpn.com lexpod click the links 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this show is also sponsored by expressvpn get it at expressvpn.com lexpod to get a discount and to support this podcast have you ever watched the office if you have you probably know it's based on the uk series also called the office not to steer up trouble but i personally think the british version is actually more brilliant than the american one but both are amazing anyway there are actually nine other countries with their own version of the office you can get access to them with no geo restriction when you use expressvpn it lets you control where you want sites to think you're located you can choose from nearly 100 different countries giving you access to content that isn't available in your region so again get it on any device at expressvpn.com lexbod to get an extra three months free and to support this podcast and now here's my conversation with russ tedjerk what is the most beautiful motion of a animal or robot that you've ever seen i think the most beautiful motion of a robot has to be the passive dynamic walkers i think there's just something fundamentally beautiful the ones in particular that steve collins built with andy rowena at cornell a 3d walking machine so it was not confined to a boom or a plane that you put it on top of a small ramp give it a little push it's powered only by gravity no controllers no batteries whatsoever it just falls down the ramp and at the time it looked more natural more graceful more human-like than any robot we'd seen to date powered only by gravity how does it work well okay the simplest model is kind of like a slinky it's like an elaborate slinky one of the simplest models we use to think about it is actually a rimless wheel so imagine taking a bike's bicycle wheel but take the rim off so it's now just got a bunch of spokes if you give that a push it still wants to roll down the ramp but every time its foot its spoke comes around and hits the ground it loses a little energy every time it takes a step forward it gains a little energy those things can come into perfect balance and actually they they want to it's a stable phenomenon if it's going too slow it'll speed up if it's going too fast it'll slow down and it comes into a stable periodic motion now you can take that rimless wheel which doesn't look very much like a human walking take all the extra spokes away put a hinge in the middle now it's two legs that's called our compass gate walker that can still you give it a little push starts falling down a ramp looks a little bit more like walking at least it's a biped but what steve and andy and ted mcgear started the whole exercise but what steve and andy did was they took it to this beautiful conclusion where they built something that had knees arms a torso the arms swung naturally uh give it a little push and that looked like a stroll through the park how do you design something like that i mean is that art or science it's on the boundary i think there's a science to getting close to the solution i think there's certainly art in the way that they they made a beautiful robot but but then the finesse because because this was work they were working with a system that wasn't perfectly modeled wasn't perfectly controlled there's all these little tricks that you have to tune the suction cups at the knees for instance so they stick but then they release at just the right time or there's all these little tricks of the trade which really are art but it was a point i mean it made the point and we were at that time the walking robot the best walking robot in the world was honda's asimo absolutely marvel of modern engineering it's 90s this was in 97 when they first released it sort of announced p2 and then it went through it was asimo by then in 2004 um and it looks like this very cautious walking like you're walking on on hot coals or something like that i think it gets a bad rap asimo is a beautiful machine it does walk with its knees bent our atlas walking had its knees bent but actually ezimo was pretty fantastic but it wasn't energy efficient neither was atlas when we worked on atlas none of our robots have that have been that complicated have been very energy efficient but there was a there's a thing that happens when you do control when you try to control a system of that complexity you try to use your motors to basically counteract gravity take whatever the world's doing to you and push back erase the dynamics of the world and impose the dynamics you want because you can make them simple and analyzable mathematically simple and this was a very sort of beautiful example that you don't have to do that you can just let go let physics do most of the work right and you just have to give it a little bit of energy this one only walked down a ramp it would never walk on the flat to walk on the flat you have to give a little energy at some point but maybe instead of trying to take the forces imparted to you by the world and replacing them what we should be doing is letting the world push us around and we go with the flow very zen very zen robot yeah but okay so that sounds very zen but you can i can also imagine how many like failed versions they had to go through like how many like i would say it's probably would you say it's in the thousands that they've had to have the system fall down before they figured out how they could i don't know if it's thousands but uh it's a lot it takes some patience there's no question so in that sense control might help a little bit oh the abs i think everybody even at the time said that the answer is to do with that with control but it was just pointing out that maybe the way we're doing control right now isn't the way we should got it so what what about on the animal side the ones that figured out how to move efficiently is there anything you find inspiring or beautiful in the movement of anybody i do have a favorite example okay so it sort of goes with the passive walking idea so is there you know how energy efficient are animals okay there's a great series of experiments by george lotter at harvard and mike tranifilo at mit they were studying fish swimming in a water tunnel okay and one of these the type of fish they were studying were these rainbow trout because they there was a phenomenon well understood that rainbow trout when they're swimming upstream at mating season they kind of hang out behind the rocks and it looks like i mean that's tiring work swimming upstream they're hanging out behind the rocks maybe there's something energetically interesting there so they tried to recreate that they put in this water tunnel a rock basically a cylinder that had the same sort of vortex street the eddies coming off the back of the rock that you would see in a stream and they put a real fish behind this and watched how it swims and the amazing thing is that if you watch from above what the fish swims when it's not behind a rock it has a particular gate you can identify the fish the same way you look at a human looking walking down the street you sort of have a sense of how human walks the fish has a characteristic gate you put that fish behind the rock its gate changes and what they saw was that it was actually resonating and kind of surfing between the vortices yeah now here was the experiment that really was the clincher because there was still it wasn't clear how much of that was mechanics of the fish how much of that is control the brain so the clincher experiment and maybe one of my favorites to date although there are many good experiments they took this was now a dead fish um they took a dead fish they put a string that went that tied the mouse of the fish to the rock so it couldn't go back and get caught in the grates uh and then they asked what would that dead fish do when it was hanging out behind the rock and so what you'd expect it sort of flopped around like a dead fish in the in the vortex wake until something sort of amazing happens and this video is worth putting in right what happens uh the dead fish basically starts swimming upstream right it's completely dead no brain no motors no control but it somehow the mechanics of the fish resonate with the vortex street and it starts swimming upstream it's one of the best examples ever who do you give credit for that too is that just evolution constantly just figuring out by killing a lot of generations of animals uh like the most efficient motion is that uh or maybe the physics of our world completely like it's like evolution applied not only to animals but just the entirety of it somehow drives to efficiency like nature likes efficiency i don't know if that question even makes any sense i understand the question that's reason i mean do they co-evolve yeah somehow yeah like i don't know if an environment can evolve but um i mean there are experiments that people do careful experiments that show that um animals can adapt to unusual situations and recover efficiency so there seems like at least in one direction i think there is reason to believe that the animal's motor system and probably its mechanics adapt in order to be more efficient but efficiency isn't the only goal of course sometimes it's too easy to think about only efficiency but we have to do a lot of other things first not get eaten and then all other things being equal try to save energy by the way let's uh draw a distinction between control and mechanics like how how can how would you define each yeah i mean i think part of the point is that we shouldn't draw a line as as clearly as we tend to but the you know on a robot we have motors and we have the links of the robot let's say if the motors are turned off the robot has some passive dynamics okay gravity does the work you can put springs i would call that mechanics right if we have springs and dampers which our muscles are springs and dampers and tendons but then you have something that's doing active work putting energy in your motors on the robot the controller's job is to send commands to the motor that add new energy into the system right so the mechanics and control interplay somewhere the divide is around you know did you decide to send some commands to your motor or did you just leave the motors off and let them do their work would you say is most of nature on the dynamic side or the control side so like if you look at biological systems if you know we're living in a pandemic now like do you think a virus is a do you think it's a dynamic system or um or is there a lot of control intelligence i think it's both but i think we maybe have underestimated how important the dynamics are right um i mean even our bodies the mechanics of our bodies certainly with exercise they evolved but so i actually i lost a finger in early 2000s and it's my fifth metacarpal it turns out you use that a lot in ways you don't expect when you're opening jars even when i'm just walking around if i bump it on something there's a bone there that was used to taking contact my fourth metacarpal wasn't used to taking contact it used to hurt it still does a little bit but actually my bone has remodeled right over the lat over a couple years the geometry the mechanics of that bone change to address the new circumstances so the idea that somehow it's only our brain that's adapting or evolving is not right maybe sticking on evolution for a bit because it's tended to create some interesting things uh by peter walking do you uh why the heck did evolution give us i think we're are we the only mammals that walk on two feet no i mean there's a bunch of animals that do it a bit there's a i think we are the most successful bypass i think some uh i think i read somewhere that um the reason the you know evolution made us walk on two feet is because uh there's an advantage to being able to carry food back to the tribe or something like that so like you can carry it's kind of this communal cooperative thing so like to carry stuff back to um to a place of shelter and so on to share with others um do you understand at all the value of uh walking on two feet from both a robotics and a human perspective yeah there are some great books written about evolution of walking evolution of the human body i think it's easy though to make bad evolutionary arguments sure most of them are probably bad but what else can we do i mean i think um a lot of what dominated our evolution probably was not the things that worked well sort of in the steady state um you know when things are when things are good but but uh for instance people talk about what we should eat now because our ancestors were meat eaters or or whatever oh yeah i love that yeah but probably you know the reason that one pre uh pre-homo sapien species versus another survived was not because of whether they ate well uh when there was lots of food but when the ice age came you know probably one of them happened to be in the wrong place one of them happened to forage a food that was okay even even when the glaciers came or something like that i mean there's a million variables that contributed and we can't and our actually the amount of information we're working with and telling these stories these evolutionary stories is uh is very little so yeah just like you said it seems like if we if we study history it seems like history turns on like these little events that uh that otherwise would seem meaningless but in the grant like when you in retrospect were turning points absolutely and that that's probably how like somebody got hit in the head with a rock because somebody slept with the wrong person back in the cave days and somebody get angry and that turned uh you know warring tribes combined with the environment all those millions of things and the meat eating which i get a lot of criticism because i i don't know um i don't know what your dietary processes are like but these days i been eating only meat which is um there's a large community people who say yeah probably make evolutionary arguments and say you do a great job there's probably an even larger community of people including my mom who says it's deeply unhealthy it's wrong but i just feel good doing it but you're right these evolutionary arguments can be flawed but is there anything interesting to pull out for um there's a great book by the way um look a series of books by nicholas taleb about fooled by randomness and black swan um highly recommend them but yeah they make the point nicely that probably it was a few random events that yes maybe it was someone getting hit by a rock as you say uh that said do you think i don't know how to ask this question or how to talk about this but there's something elegant and beautiful about moving on two feet obviously biased because i'm human but from a robotics perspective too you work with robots on two feet is it um is it all useful to build robots that are on two feet as opposed to four is there something useful about it the most um i mean the reason i spent a long time working on bipedal walking was because it was hard and it was um it challenged control theory in ways that i thought were important um i wouldn't have ever tried to convince you that you should start a company around bipeds or something like this there are people that make pretty compelling arguments right i think the most compelling one is that the world is built for the human form and if you want a robot to work in the world we have today then you know having a human form is a pretty good way to go there there are places that a biped can go that would be hard for other form factors to go even natural places but um you know at some point in the long run we'll be building our environments for our robots probably and so maybe that argument falls aside so you famously run barefoot do you still run barefoot i still run barefoot that's so awesome much to my wife's chagrin do you want to make an evolutionary argument for why running barefoot is advantageous um what have you learned about um human and robot movement in general from running barefoot human or robot and or well you know it happened the other way right so i was studying walking robots and i was there's a great conference called the dynamic walking conference where it brings together both the biomechanics community and the walking robots community and so i've been going to this for years and hearing talks by people who study barefoot running and other the mechanics of running so i i did eventually read born to run most people read born to run in the first thing right the other thing i had going for me is actually that i i wouldn't i wasn't a runner before and i learned to run after i had learned about barefoot running i mean started running longer distances so i didn't have to unlearn and i'm definitely um i'm a big fan of it for me but i'm not gonna i tend to not try to convince other people there's people who run beautifully with shoes on and that's good um but here's why it makes sense for me um it's all about the long-term game right so i think it's just too easy to run 10 miles feel pretty good and then you get home at night and you realize uh my knees hurt i did something wrong right um if you take your shoes off then if you hit hard with your foot at all um then it hurts you don't like run 10 miles and then and then realize you've done something some damage you have immediate feedback telling you that you've done something that's that's maybe sub-optimal and you change your gait i mean it's even subconscious if i right now having run many miles barefoot if i put a shoe on my gate changes in a way that i think is not as good um so so it makes me land softer and i think my my goals for running are to do it for as long as i can into old age um not to win any races and so for me this is a you know a way to protect myself yeah i think um first of all i've tried running barefoot many years ago uh probably the other way just just just uh reading born to run but just to understand because i felt like i couldn't put in the miles that i wanted to and it feels like running for me and i think for a lot of people was one of those activities that we do often and never really try to learn to do correctly like it's funny there's so many activities we do every day like brushing our teeth right i think a lot of us at least me probably have never deeply studied how to properly brush my teeth right or wash as now with a pandemic or how to properly wash our hands or do it every day but we haven't really studied like am i doing this correctly but running felt like one of those things it was absurd not to study how to do correctly because it's the source of so much pain and suffering like i hate running but i do it i do it because i hate it but it i feel good afterwards but i think it feels like you need to learn how to do it properly so that's where barefoot running came in and then i quickly realized that my gait was completely wrong i was taking huge like steps and landing hard on the heel all those elements and so yeah from that i actually learned to take really small steps look i already forgot the number but i feel like it was 180 a minute or something like that and i remember i was uh i actually just took songs that are 180 beats per minute and then like tried to run at that beat uh just to teach myself it took took a long time and i feel like uh after a while you learn to run you adjust it properly without going all the way to barefoot but i feel like barefoot is the legit way to do it i mean i think a lot of people would be really curious about it can you if they're interested in trying what would you how would you recommend a start or try or explore slowly that's the biggest thing people do is they are excellent runners and they're used to running long distances or running fast and they take their shoes off and they hurt themselves instantly trying to do something that they were used to doing i i think i lucked out in the sense that i i couldn't run very far when i first started trying and i run with minimal shoes too i mean i will you know bring along a pair of actually like aqua socks or something like this i can just slip on or running sandals i've tried all of them what's the difference between a minimal shoe and nothing at all what's like feeling wise what does it feel like there is i mean i noticed my gate changing right so um i mean your your foot has as many muscles and sensors as your hand does right sensors ooh okay and we do amazing things with our hands and we stick our foot in a big solid shoe right so there's i think you know when you're barefoot you're you're just giving yourself more proprioception and that's why you're more aware of some of the gait flaws and stuff like this now you have less protection too so um rocks and stuff i mean yeah so so i think people are who are afraid of barefoot running they're worried about getting cuts or getting stepping on rocks first of all even if that was a concern i think those are all like uh very short-term you know if i get a scratch or something it'll heal in a week if i blow out my knees i'm done running forever so i will trade the short term for the long term anytime but even then you know this again to my wife's chagrin um your feet get tough right and uh uh cows okay yeah i can run over almost anything now i mean what uh maybe can you talk about is there tin like is there tips or tricks that you have uh suggestions about like if i wanted to try it you know there is a good book actually uh there's probably more good books since i read them but uh ken bob barefoot ken bob saxton um he's an interesting guy but i think his book captured uh the right way to describe running barefoot running to somebody better than any other i've seen so you run pretty good distances and you bike and is is there um you know if we talk about bucket list items is there something crazy on your bucket list athletically that you hope to do one day i mean my commute is already a little crazy um what are we talking about here what what uh what distance are we talking about well i live about 12 miles from mit but you can find lots of different ways to get there so i mean i've run there for a long many years a bike there um blaze yeah but normally i would try to run in and then bike home bike in run home but you have run there and back before sure barefoot yeah uh yeah or with minimal shoes or whatever that 12 12 times two yeah okay it became kind of a game of how can i get to work i've rollerbladed i've done all kinds of weird stuff but uh my favorite one these days is i've been taking the charles river to work so i can put in a little row boat not so far from my house but the charles river takes a long way to get to mit so i can spend a long time getting there and it's you know it's not about i don't know it's just about uh i've had people ask me how can you justify taking that time uh but for me it's just a magical time to think to compress decompress um you know especially i'll wake up do a lot of work in the morning and then i kind of have to just let that settle before i i'm ready for all my meetings and then on the way home it's a great time to load it sort of let that settle so you you lead a like a a large group of people i mean you're is there days where you're like oh shit i gotta get to work in an hour like i i mean uh is is there is there a tension there where and like if we look at the grand scheme of things just like you said long term that meeting probably doesn't matter like you can always say i'll just i'll run and let the meeting happen how it happens like what uh how do you that zen how do you uh what do you do with that tension between the real world saying urgently you need to be there this is important everything is melting down how we're going to fix this robot there's this uh critical meeting and then there's this the zen beauty of just running the simplicity of it you along with nature what do you do with that i would say i'm not a fast runner particularly probably my fastest splits ever was when i had to get to daycare on time because they were going to charge me you know some some dollar per minute that i was late uh i've run some fast splits to daycare but that those times are passed now i think work you can find a work-life balance in that way i think you just have to i think i am better at work because i take time to think on the way in so i plan my day around it and i i rarely feel that those are really in at odds so what the bucket list item if we're talking 12 times 2 or approaching a marathon uh what uh have you run an ultra marathon before do you do races is there what's uh to win i'm not gonna like take a dinghy across the atlantic or something if that's what you want but uh uh but if someone does and wants to write a book i would totally read it because i'm a sucker for that kind of thing no i do have some fun things that i will try you know i like to when i travel i almost always bike to logan airport and fold up a little folding bike on and then take it with me and bike to wherever i'm going and i've it's taken me or i'll take a stand-up paddleboard these days on the airplane and then i'll try to paddle around where i'm going or whatever and i've done some crazy things but um but not for the you know i've i now talk i don't know if you know who david goggins is by any chance not well but yeah but i i talk to him now every day so he's the person who made me uh do this stupid challenge so he he's insane and he does things for the purpose in in the best kind of way he does things like for the explicit purpose of suffering like he picks the thing that like whatever he thinks he can do he does more uh so is that do you have that thing in you or you uh i think it's become the opposite it's uh so you're like that dynamical system that the walker the efficient uh yeah it's uh leave no pain right you should end feeling better than you started okay but um it's mostly i think and kovit has tested this because i've lost my commute i think i'm perfectly happy walking around uh around town with my wife and uh kids if they could get them to go and it's more about just getting outside and getting away from the keyboard for some time just to let things compress let's go into robotics a little bit what to use the most beautiful idea in robotics whether we're talking about control or whether we're talking about optimization the math side of things or the engineering side of things or the philosophical side of things i think i've been lucky to experience something that not so many roboticists have experienced which is to hang out with some really amazing control theorists and uh the clarity of thought that some of the more mathematical control theory can bring to even very complex messy looking problems is really it really had a big impact on me and and uh i had a day even like just a couple weeks ago where i had spent the day on a zoom robotics conference having great conversations with lots of people i felt really good about the ideas that were flowing and and the like and then i had a you know late afternoon meeting with uh one of my favorite control theorists and um and we went from these from these abstract discussions about maybes and what-ifs and and what a great idea to these super precise statements about systems that aren't that much more simple or or abstract than the ones i care about deeply and the contrast of that is um i don't know it really gets me i think people underestimate um maybe the power of clear thinking and so for instance deep learning is amazing um i use it heavily in our work i think it's changed the world unquestionable it makes it easy to get things to work without thinking as critically about it so i think one of the challenges as an educator is to think about how do we make sure people get a taste of the more rigorous thinking that i think goes along uh with with some different approaches yeah so that's really interesting so understanding like the fundamentals the first principles of the of the the the problem where in this case is mechanics like how a thing moves how thing behaves like all the forces involved like really getting a deep understanding of that i mean from physics the first principle thing come from physics and here it's literally physics yeah and this applies in deep learning this applies to um not just i mean it applies so cleanly in in robotics but it also applies to just in any data set i find this true i mean driving as well there's a lot of folks in it that work on autonomous vehicles that don't study driving like deeply i i might be coming a little bit from the psychology side but i remember i spent a ridiculous number of hours at lunch at this like lawn chair and i would sit somewhere somewhere on mit's campus there's a few interesting intersections and we just watched people cross so we were studying um pedestrian behavior and i felt like as you record a lot of video to try and just the computer vision extracts their movements how they move their head and so on but like every time i felt like i didn't understand enough i i just i felt like i wasn't understanding what how are people signaling to each other what are they thinking how cognizant are they of their fear of death like what we like what's the game what's the underlying game theory here what are what are the the the incentives and then i finally found a live stream uh of an intersection that's like high def that i just i would watch so i wouldn't have to sit out there but that's interesting so like that's tough that's a tough example because i mean the learning humans are involved not just because human but i think um the learning mantra is the basically the statistics of the data will tell me things i need to know right and you know for the example you gave of all the nuances of um you know eye contact or hand gestures or whatever that are happening for these subtle interactions between pedestrians and traffic right maybe the data will tell us they'll tell that story i may be even i uh one level more meta than than what you're saying for a particular problem i think it might be the case that data should tell us the story but i think there's a rigorous thinking that is just an essential skill for a mathematician or an engineer that um i just don't want to lose it yes there are there are certainly super rigorous um rigorous control oh sorry machine learning people i just think deep learning makes it so easy to do some things that um our next generation are um not immediately rewarded for going through some of the more rigorous approaches and i wonder where that takes us i just well i'm actually optimistic about it i just want to do my part to try to steer that rigorous thinking so there's like two questions i want to ask do you have sort of a good example of rigorous thinking where it's easy to get lazy and not do the rigorous thinking and the other question i have is like do you have advice of um how to practice rigorous thinking and um you know in all the computer science disciplines that we've mentioned yeah i mean there are times where problems that can be solved with well-known mature methods could also be solved with with a deep learning approach and there's an argument that you must use learning even for the parts we already think we know because if the human has touched it then you've if you've biased the system and you've suddenly put a bottleneck in there that is your own mental model but something like inverting a matrix you know i i think we know how to do that pretty well even if it's a pretty big matrix and we understand that pretty well and you could train a deep network to do it but you shouldn't probably so so in that sense rigorous thinking is uh understanding the the scope and the limitations of the mess of the methods that we have like how to use the tools of mathematics properly yeah i think you know taking a class on analysis is all i'm sort of arguing is to take take a chance to stop and and force yourself to think rigorously about even you know the rational numbers or something you know it doesn't have to be the end-all problem but that exercise of clear thinking i think uh goes a long way and i just want to make sure we we keep preaching don't lose it yeah but do you think uh when you're doing like rigorous thinking or like maybe uh trying to write down equations or sort of explicitly like formally describe a system do you think we naturally simplify things too much is that a danger you run into like uh in order to be able to understand something about the system mathematically we uh make it too much of a toy example but i think that's the good stuff right um that's how you understand the fundamentals i think so i think maybe even that's a key to intelligence or something but i mean okay what if newton and galileo had deep learning and and they had done a bunch of experiments and they told the world here's your weights of your neural network i've we've solved the problem yeah you know where would we be today i don't i don't think we'd be as far as we as we are there's something to be said about having a the simplest explanation for a phenomenon so i don't doubt that we can train neural networks to predict even physical you know f equals m a type equations but um i maybe i want another newton to come along because i think there's more to do in terms of coming up with the simple models for more complicated tasks yeah uh let's not offend the ai systems from 50 years from now that are listening to this that are probably better at might be better coming up with f equals m a equations themselves so sorry i actually think um learning is probably a route to achieving this but the representation matters right and i think having a function that takes my inputs to outputs that is arbitrarily complex may not be the end goal i think there's still you know the most simple or parsimonious explanation for the data simple doesn't mean low dimensional that's one thing i think that we've a lesson that we've learned so you know a standard way to do model reduction or system identification and controls is to the typical formulation is that you try to find the minimal state dimension realization of a system that hits some error bounds or something like that and that's maybe not i think we're we're learning that that was that the state dimension is not the right metric of complexity of complexity but for me i think a lot about contact the mechanics of contact the robot hand is picking up an object or something and when i write down the equations of motion for that they're they look incredibly complex not because actually not so much because of the dynamics of the hand when it's moving but it's just the interactions and when they turn on and off right so having a high dimensional you know but simple description of what's happening out here is fine but if when i actually start touching i write down a different dynamical system for every polygon on my robot hand and every polygon on the object whether it's in contact or not with all the combinatorics that explodes there then that's too complex so i need to somehow summarize that with a more intuitive physics way of thinking and yeah i'm very optimistic that machine learning will get us there first of all i mean i'll probably do it in the introduction but you're one of the great robotics people at mit you're a professor at mit you've teach them a lot of amazing courses you run a large group and you have a important history for mit i think as being a part of the darpa robotics challenge can you maybe first say what is the dark robotics challenge and then tell your story around it your journey with it yeah sure um so the darpa robotics challenge it came on the tales of the darpa grand challenge and darpa urban challenge which were the challenges that brought us put a spotlight on self-driving cars guild pratt was at darpa and pitched a new challenge that involved disaster response it didn't explicitly require humanoids although humanoids came into the picture this happened shortly after the fukushima disaster in japan and our challenge was motivated roughly by that because that was a case where if we had had robots that were ready to be sent in there's a chance that we could have averted disaster and certainly after the um in the disaster response there were times we would love we would have loved to have sent robots in so in practice what we ended up with was a grand challenge a darpa robotics challenge where boston dynamics was was to make humanoid robots people like me and the the amazing team at mit were competing first in a simulation challenge to try to be one of the ones that wins the right to work on one of the uh the boston dynamics humanoids in order to compete in the the final challenge which was a physical challenge and at that point it was already so it was decided as humanoid robots there were there were two tracks there you could enter as a hardware team where you brought your own robot or you could enter through the virtual robotics challenge as a software team that would try to win the right to use one of the boston dynamics robots which are called atlas atlas humanoid robots yeah it was a 400-pound marvel but a you know pretty big scary looking robot expensive too expensive at the time yeah okay so uh i mean how did you feel at the prospect of this kind of challenge i mean it seems you know autonomous vehicles yeah i guess that sounds hard but uh not really from a robotics perspective it's like didn't they do in the 80s is the kind of feeling i would have uh like when you first look at the problem it's on wheels but like humanoid robots that sounds really hard so what like what are your the psychologically speaking what were you feeling excited scared why the heck did you get yourself involved in this kind of messy challenge we didn't really know for sure what we were signing up for in the sense that you could have something that as it was described in the call for participation that could have put a huge emphasis on the dynamics of walking and not falling down and walking over rough terrain or the same description because the robot had to go into this disaster area and turn valves and and pick up a drill cut the hole through a wall it had to do some interesting things the challenge could have really highlighted perception and autonomous planning or it ended up that you know locomoting over a complex terrain played a pretty big role in the competition so and the degree of autonomy wasn't clear the decree of autonomy was always a central part of the discussion so um what wasn't clear was how we would be able how far we'd be able to get with it so the idea was always that you want semi-autonomy that you want the robot to have enough compute that you can have a degraded network link to a human and so the same way you we had degraded networks at many natural disasters you'd send your robot in you'd be able to get a few bits back and forth but you don't get to have enough potentially to fully uh operate the robot in every joint of the robot so and then the question was and the gamesmanship of the organizers was to figure out what we're capable of push us as far as we could so that um it would differentiate the teams that put more autonomy on the robot and had a few clicks and just said go there do this go there do this versus someone who's picking every footstep or something like that so what were some memories painful triumphant from the experience like what was that journey maybe if you can dig in a little deeper maybe even on the technical side and the team side that that whole process of um from the early idea stages to actually competing i mean this was a defining experience for me i i it was it came at the right time for me in my career i had gotten tenure before i was do a sabbatical and most people do something you know relaxing and restorative for a sabbatical so you got tenure before the the before this yeah yeah yeah it was a good time for me i had i had we had a bunch of algorithms that we were very happy with we wanted to see how far we could push them and this was a chance to really test our metal to do more proper software engineering the team we all just worked our butts off we you know we're in that lab almost all the time okay so i mean there were some of course high highs and low lows throughout that anytime you're you know not sleeping and devoting your life to a 400 pound humanoid um i remember actually one funny moment where we're all super tired and so atlas had to walk across cinder blocks that was one of the obstacles and i remember atlas was powered down and hanging limp you know on the on its harness and the the humans were there like laying you know picking up and laying the brick down so that the robot could walk over it and i thought what is wrong with this you know we've got a robot just watching us do all the manual labor so that it can take its little um stroll across the train but i mean even the even the virtual robotics challenge was was super nerve-wracking and dramatic i remember um so so we were using gazebo as a simulator uh on the cloud there was all these interesting challenges i think um the investment that that osrs fc whatever they were called at that time brian gerkey's team at open source robotics um they were pushing on the capabilities of gazebo in order to scale it to the complexity of these challenges so um you know up to the virtual competition so the virtual competition was you will sign on at a certain time and we'll have a network connection to another machine on the cloud that is running the simulator of your robot and your controller will run on this this controller this computer and and the physics will run on the other and you have to connect now um the physics they wanted it to run at real-time rates because there was an element of human interaction um and humans could if you do want to tell the op it works way better if it's at frame rate oh cool but it was very hard to simulate these comple these complex scenes at real-time rate so right up to like days before the competition the the simulator wasn't quite at real time rate and that was great for me because my controller was solving a big pretty big optimization problem and it wasn't quite at real-time rate so i was fine i was keeping up with the simulator we were both running at about 0.7 and i remember getting this email and by the way the perception folks on our team hated that that they knew that if my controller was too slow the robot was going to fall down and and you know no matter how good their perception system was if i can't make my controller fast anyways we get this email like three days before the virtual competition well you know it's for all the marbles we're going to either get a humanoid robot or we're not and we get an email saying good news we made the robot does the simulator faster it's now one point and uh yeah we're i was just like oh man what are we going to do here so yeah that came in late at night for me um a few days ahead a few days ahead i went over there was it happened that frank permentor who's a a very very sharp he's a he was a student at the time working on optimization was he was still in lab uh frank we need to make this quadratic programming solver faster not like a little faster it's actually you know um and we wrote a new solver for that qp together that night and you start terrifying so there's a really hard optimization problem that you're constantly solving you didn't make the optimization problem simpler you you wrote any solver so um i mean your observation is almost spot on well what we did was what everybody i mean people know how to do this but we had not yet done this idea of warm starting so we are solving a big optimization problem at every time step but if you're running fast enough the optimization problem you're solving on the last time step is pretty similar to the optimization you're going to solve with the next we had course had told our commercial solver to use warm starting but even the interface to that commercial solver was causing us these delays so what we did was we basically wrote we called it fastqp at the time we wrote a very lightweight very fast layer which would basically check if nearby solutions to the quadratic program were which were very easily checked uh could stabilize the robot and if they couldn't we would fall back to the solver you couldn't really test this well right um or like i mean so we always knew that if we fell back if we it got to the point where if for some reason things slowed down and we fell back to the original solver the robot would actually literally fall down um so it was it was a harrowing sort of edge we're ledge we were sort of on but i mean actually like the the 400 pound humor could come crashing to the ground if you if you if your solver is not fast enough but you know that we have lots of good experiences so can i ask you a weird question i i get um about idea of hard work so um actually people like students of yours that i've interacted with and just and robotics people in general but they uh they have moments at moments have worked harder than uh most people i know in terms of if you look at different disciplines of how hard people work but they're also like the happiest like just like i don't know um it's the same thing with like running people that push themselves to like the limit they all also seem to be like the most like full of life somehow uh and i get often criticized like you're not getting enough sleep what are you doing to your body blah blah blah like this kind of stuff and i usually just kind of respond like i'm i'm doing what i love i'm passionate about i love it i feel like it's it's invigorating i actually think i don't think the lack of sleep is what hurts you i think what hurts you is uh stress and lack of doing things that you're passionate about but in this world yeah i mean can you comment about uh why the heck robotics people are uh willing to push themselves to that degree is there value in that and why are they so happy i think i think you got it right i mean i think the causality is not that we work hard and i think other disciplines work very hard too but it's i don't think it's that we work hard and therefore we are happy i think we found something that we're truly passionate about it makes us very happy and then we get a little involved with it and spend a lot of time on it um what a luxury to have something that you want to spend all your time on right we could talk about this for many hours but maybe if we could pick is there something on the technical side on the approach you took that's interesting that turned out to be a terrible failure or a success that you carry into your work today about all the different ideas that were involved in um making whether in the in the simulation or in the in the real world making this semi-autonomous system work i mean it really did teach me something fundamental about what it's going to take to get robustness out of a system of this complexity i would say the darpa challenge really was foundational in my thinking i think the autonomous driving community thinks about this i think lots of people thinking about safety critical systems that might have machine learning in the loop are thinking about these questions for me the darpa challenge was the moment where i realized you know we've spent every waking minute running this robot and again the in for the physical competition days before the competition we saw the robot fall down in a way it had never fallen down before i thought you know how could we have found that you know we only have one robot it's running almost all the time we just didn't have enough hours in the day to test that robot something has to change right and then i think that i mean i would say that the team that won was was from kaist was the team that had two robots and was able to do not only incredible engineering just absolutely top-rate engineering but also they were able to test at a rate and um discipline that we didn't keep up with what does testing look like what are we talking about here like what's what's a a loop of test like a from start to finish what is a loop of testing yeah i mean i think there's a whole philosophy to testing there's the unit tests and you can do that on a hardware you can do that in a small piece of code you write one function you should write a test that that checks that function's input outputs you should also write an integration test at the other extreme of of running the whole system together you know where that that try to turn on all the different functions that you've you think are correct it's much harder to write the specifications for a system level test especially if that system is as complicated as a humanoid robot but the philosophy is sort of the same i'm the real robot it's it's no different but on a real robot it's impossible to run the same experiment twice so if you if you see a failure you hope you caught something in the logs that tell you what happened but you'd probably never be able to run exactly that experiment again and right now i think our philosophy is just basically monte carlo estimation is just run as many experiments as we can maybe try to set up the environment to to make the things we are worried about happen as often as possible but really we're relying on somewhat random search in order to test maybe that's all we'll ever be able to but i think uh you know because there's an argument that the things that will get you are the the things that are really nuanced in the world and it'd be very hard to for instance put back in a simulation yeah the i guess the edge cases what was the the hardest thing like so you said walking over rough terrain like the just taking footsteps i mean people there's it's so dramatic and painful in a certain kind of way to watch these videos from the drc of robots falling yep it's just so heartbreaking i don't know maybe it's because for me at least we anthropomorphize the robot um of course there's everything funny for some reason like humans falling is funny uh for i don't it's some dark reason i'm not sure why it is so but it's also like tragic and painful and uh so speaking of which i mean what what made the robots fall and fail uh in your view so i can tell you exactly what happened on our we i contributed one of those our team contributed one of those spectacular falls every one of those falls the has a complicated story i mean one time the power effectively went out on the robot because it had been sitting at the door waiting for a green light to be able to proceed and its batteries you know and therefore it just fell backwards and smashed its head across ground and it was hilarious but it wasn't because of bad software right um but for ours so the hardest part of the challenge the hardest task in my view was getting out of the polaris it was actually relatively easy to drive the polaris we have can you tell the stars no the story of the car [Laughter] people should watch this video i mean the the the thing you've come up with is just brilliant but uh anyway sorry what's uh yeah we we kind of joke we call it the big robot little car problem because um somehow the race organizers decided to give us a 400 pound humanoid and they also provided the vehicle which was a little polaris and the robot didn't really fit in the car so you couldn't drive the car with your feet under the steering column we actually had to straddle the the main column of the uh and have basically one foot in the passenger seat one foot in the driver's seat and then drive with our left hand but the hard part was we had to then park the car get out of the car uh it didn't have a door that was okay but it's just uh getting up from crouched from sitting when you're in this very constrained environment uh first of all i remember after watching those videos i was much more cognizant of how hard is it it is for me to get in and out of the car and out of the car especially like it's actually a really difficult control problem yeah and i i'm very cognizant of it when i'm like injured for whatever reason it's really hard yeah so so how did you how did you approach so so we had a you know you think of um nasa's operations and they have these checklists you know pre-launch checklists and they're like we weren't far off from that we had this big checklist and on the first day of the competition we were running down our checklist and one of the things we had to do we had to turn off the controller the piece of software that was running that would drive the left foot of the robot in order to accelerate on the gas and then we turned on our balancing controller and the nerves jitters of the first day of the competition someone forgot to check that box and turn that controller off so um we used a lot of motion planning to figure out a a sort of configuration of the robot that we get up and and over we relied heavily on our balancing controller and and basically there was when the robot was in one of its most precarious you know sort of configurations trying to sneak its big leg out of the out of the side the other controller that thought it was still driving told its left foot to go like this and uh and that wasn't good um but but it turned disastrous for us because um what happened was a little bit of push here actually if you we have videos of us you know running into the robot with a 10-foot pole and it kind of will recover but this is a case where there's no space to recover so a lot of our secondary balancing mechanisms about like take a step to recover they were all disabled because we were in the car and there's no place to step so we're relying on our just lowest level reflexes and even then i think just hitting the foot on the seat on the on the floor we probably could have recovered from it but the thing that was bad that happened is when we did that and we jostled a little bit the tailbone of our robot hat was only a little off the seat it hit the seat and the other foot came off the ground just a little bit and nothing in our plans had ever told us what to do if your butt's on the seat and your feet are in the air feeding air and then the thing is once you get off the script things can go very wrong because even our state estimation our system that was trying to collect all the data from the sensors and understand what's happening with the robot it didn't know about this situation so it was predicting things that were just wrong and then we did a violent shake and fell off in our uh face first on out of the robot but like into the destination that's true we fell in we got our point for egress but so uh is there any hope for that's interesting is there any hope for uh atlas to be able to do something when it's just on its butt and feet in the air absolutely so you can no so that's um that is one of the big challenges and i think it's still true um you know boston dynamics and and um animal and there's this incredible work on on legged robots happening around the world most of them still are are very good at the case where you're making contact with the world at your feet and they have typically point feet relatively they're balls on their feet for instance if that if those robots get in a situation where the elbow hits the wall or something like this that's a pretty different situation now they have layers of mechanisms that will make i think the the more mature solutions have have ways in which the controller won't do stupid things but a human for instance is able to leverage incidental contact in order to accomplish a goal in fact i might if you push me i might actually put my hand out and make a new brand new contact the feet of the robot are doing this on quadrupeds but we mostly in robotics are afraid of contact on the rest of our body which is crazy there's this whole field of motion planning collision-free motion planning and we write very complex algorithms so that the robot can dance around and make sure it doesn't touch the world um so people are just afraid of contact because contact is seen as a difficult it's still a difficult control problem and sensing problem now you're a serious person uh i'm a little bit of an idiot and i'm going to ask you some dumb questions uh so i do uh i do martial arts uh so like jiu jitsu there's wrestled my whole life so let me let me ask the question um you know like whenever people learn that i do any kind of ai or like i mention robots and things like that they say when am i gonna have robots that um you know that can win in a wrestling match or in a fight against a human so we just mentioned sitting on your butt if you in the air that's a common position jiu jitsu when you're on the ground you're when you're down opponent um like what how difficult do you think is the problem and when will we have a robot that can defeat a human in a wrestling match and we're talking about a lot like if i don't know if you're familiar with wrestling but essentially um not very it's basically the art of contact it's like it's because you're you're you're picking contact points and then using like leverage like to uh off balance to to trick people like you uh make them feel like you're doing one thing and then they they change their balance and then you uh switch what you're doing and then results in a throw or whatever so like it's basically the art of multiple contacts so awesome that's a nice description of it so there's also an opponent in there right so so if very dynamic right if you are wrestling a human and uh are in a game theoretic situation with a human that's still hard but just to speak to the you know quickly reasoning about contact part of it for instance yeah maybe even throwing the game theory out of it almost like uh yeah almost like a non-dynamic opponent right there's reasons to be optimistic but i think our best understanding of those problems are still pretty hard um i have been increasingly focused on manipulation partly where that's a case where the contact has to be much more rich and there are some really impressive examples of of deep learning policies controllers that that can appear to do good things through contact we've even got new examples of of you know deep learning models of predicting what's going to happen to objects as they go through contact but i think the challenge you just offered there still eludes us right the ability to make a decision based on those models quickly you know i have to think though it's hard for humans too when you get that complicated i think probably you had maybe a slow-motion version of where you learn the basic skills and you've probably gotten better at it and and um there's there's much more subtlety but it might still be hard to actually you know really on the fly take a you know model of your humanoid and figure out how to how to plan the optimal sequence that might be a problem we never solve well the rapid the i mean one of the most amazing things to me about the we could talk about martial arts uh we could also talk about dancing it doesn't really matter too human i think it's the most interesting study of contact it's not even the dynamic element of it it's the like when you get good at it it's so effortless like i can just i'm very cognizant of the entirety of the learning process being essentially like learning how to move my body in a way that i could throw very large weights around effortlessly like and and i can feel the learning like i'm a huge believer in drilling of techniques and you can just like feel your i don't you're not feeling you're feeling um sorry you're learning it intellectually a little bit but a lot of it is the body learning it somehow uh like instinctually and whatever that learning is that's really i'm not even sure if that's um equivalent to uh like a deep learning learning a controller i think it's something more it feels like there's a lot of distributed learning going on yeah i think there's hierarchy and composition yeah um probably in the systems that we don't capture very well yet uh you have layers of control systems you have reflexes at the bottom layer and you have a you know a system that's capable of planning a vacation to some distant country which is probably you probably don't have a controller a policy for every possible destination you'll ever pick right um but there's something magical in the in between and how do you go from these low-level feedback loops to something that feels like a pretty complex set of outcomes you know my guess is i think i think there's evidence that you can plan at some of these levels right so uh josh tenenbaum just showed it in his talk the other day he's got a game he likes to talk about i think he calls it the pick 3 game or something where he puts a bunch of clutter down in front of a person and he says okay pick three objects and it might be a telephone or a shoe or a kleenex box or whatever and apparently you pick three items and then you pick he says okay pick the first one up with your right hand the second one up with your left hand now using those objects those now as tools pick up the third object right so that's down at the level of of physics and mechanics and contact mechanics that that i think we do learning we do have policies for we do control for almost feedback but somehow we're able to still i mean i've never picked up a telephone with a shoe and a water bottle before and somehow and it takes me a little longer to do that the first time but most of the time we can sort of figure that out so yeah i think the amazing thing is this ability to be flexible with our models plan when we need to use our well-oiled controllers when we don't when we're in familiar territory um having models i think the the other thing you just said was something about i think your awareness of what's happening is even changing as you as you get as you improve your expertise right so maybe you have a very approximate model of the mechanics to begin with and as you gain expertise you get a more refined version of that model you're aware of muscles or balance components that you just weren't even aware of before so how do you scaffold that yeah plus the fear of injury the ambition of goals of excelling and uh fear of mortality let's see what else is in there as the motivations uh overinflated ego in the beginning uh like and then a crash of confidence in the middle all of those seem to be essential for the learning process and also and if all that's good then you're probably optimizing energy efficiency yeah right so we have to get that right uh so um you know there was this idea that you would have uh robots play soccer better than human players by 2050 that was the goal uh world basically was the goal to beat world champion team to become a world cup be like a world cup right level team so are we gonna see that first or um a robot if you're familiar there's an organization called ufc for mixed martial arts are we going to see a world cup championship soccer team out of robots or a ufc champion mixed martial artist uh that's a robot i mean it's very hard to to say one thing is a harder one some problems harder than the other what probably matters is um who who who started the organization that that i mean i think robocup has a pretty serious following and there is a history now of people playing that game learning about that game building robots to play that game building increasingly more human robots it's got momentum and so if you want to uh to have mixed martial arts compete you better start your start your organization now right um i think almost independent of which problem is technically harder because they're both hard and they're both different that's a good point i mean those videos are just hilarious like uh especially the humanoid robots trying to um trying to play soccer i mean they're kind of terrible right now i mean i guess there is robo sumo wrestling there's like the robo one competitions um where they do have these robots that go on the table and basically fight so maybe i'm wrong maybe first of all do you have a year in mind for uh robocup just from a robotics perspective it seems like a super exciting possibility that um like in the physical space this is what's interesting i think the world is captivated i think it's really exciting it's um it inspires a huge number of people when a machine beats a human at a game that humans are really damn good at so you're talking about chess and go but that's in the in the world of uh digital i don't think machines have beat humans at a game in the physical space yet but that would be just you have to make the rules very carefully right i mean if if atlas kicked me in the shins i'm down and uh you know and and game over so there's you know it's it's very subtle on yeah i think that's fair i think the fighting one is a weird one yeah because uh you're talking about a machine that's much stronger than you but yeah in terms of soccer basketball all those kinds of soccer right i mean as soon as there's contact or whatever and there's there are some things that the robot will do better i think if you really set yourself up to try to see could robots win the game of soccer as the rules were written the right thing for the robot to do is to play very differently than a human would play it's you're not going to get you know the perfect soccer player robot you're going to get something that exploits the rules exploits its super actuators it's super low bandwidth um you know feedback loops or whatever and it's going to play the game differently than you want it to play yeah um and it i bet there's ways there's i bet there's loopholes right we saw that in the in the darpa challenge that that it's very hard to write a set of rules that someone can't find uh a way to exploit let me ask another ridiculous question i promise i think this might be the last ridiculous question but i doubt it i i aspire to ask as many uh ridiculous questions of uh of a brilliant mit professor okay uh i don't know if you've seen the black mirror it's funny i i never watched the episode i know when it happened though because i gave a talk to some mit faculty one day on a unassuming you know monday or whatever i was telling about the state of robotics and i showed some video of from boston dynamics of the quadruped spot at the time it was the early version of spot and there was a look of horror that went across the room and i said what you know i've shown videos like this a lot of times what happened and it turns out that this video had gone yeah this black mirror episode had changed the way people watched um yeah the videos i was putting out the way they see these kinds of robots so i talked to so many people who are just terrified because of that episode probably of these kinds of robots they i almost want to say they almost kind of like enjoy being terrified i don't even know what it is about human psychology that kind of imagine doomsday the destruction of the universe or our society and kind of like enjoy being afraid um i don't want to simplify it but it feels like they talk about it so often it almost there does seem to be an addictive quality to it um i talked to a guy that says this a guy named joe rogan who's kind of the flag bearer for being terrified of these robots uh do you have a two questions one do you have an understanding of why people are afraid of robots and the second question is uh in black mirror just to tell you the episode i don't even remember it that much anymore but these robots i think they can shoot like a pellet or something they basically have it's basically a spot with a gun and um how far are we away from having robots that go rogue like that you know basically spot that goes rogue for some reason and somehow finds a gun right so i mean i'm i'm not a psychologist um i think i don't know exactly why people react the way they do i think i think we have to be careful about the way robots influence our society and the like i think that's something that's a responsibility that roboticists need to embrace i don't think robots are going to come after me with a kitchen knife or a pellet gun right away and i mean if they were programmed in such a way but i used to joke with atlas that all i had to do was run for five minutes and it's battery would run out but uh actually they've got a very big battery in there by the end so it was over an hour um i think the fear is a bit cultural though because i i mean you notice that like i think in my age in the u.s we grew up watching terminator right if i had grown up at the same time in japan i probably would have been watching astro boy and there's a very different reaction to robots in different countries right so i don't know if it's a human innate fear of metal marvels or if it's something that we've done to ourselves with our sci-fi yeah the stories we tell ourselves through uh through movies through just uh through popular media but if if i were to tell you know if if you were my therapist and i said i'm really terrified that we're going to have these robots very soon that will hurt us like how do you approach making me feel better like why shouldn't people be afraid there's a i think there's a video that went viral recently everything everything was spot in boston today which goes viral in general but usually it's like really cool stuff like they're doing flips and stuff or like sad stuff would be it's atlas being hit with a broomstick or something like that but uh there's a video where i think uh one of the new production spot robots which are awesome it was like patrolling somewhere in like in some country and like people immediately were like saying like this is like the dystopian future like the surveillance state for some reason like you can just have a camera like something about spot being able to walk on four feet with like really terrified people so like what what do you say to those people i think there is a legitimate fear there because so much of our future is uncertain but at the same time technically speaking it seems like we're not there yet so what do you say i mean i think technology is um complicated it can be used in many ways i think there are purely software um attacks that somebody could use to do great damage maybe they have already um you know i think uh wheeled robots could be used in bad ways too drones right um i don't think that let's see i don't want to be um building technology just because i'm compelled to build technology and i don't think about it but i would consider myself a technological optimist i guess um in the sense that i think we should continue to create and evolve and our world will change um and if we will introduce new challenges we'll screw something up maybe but i think also we'll invent ourselves out of those challenges and life will go on so it's interesting because you didn't mention like this is technically too hard i don't think robots are i think people attribute a robot that looks like an animal as maybe having a level of self-awareness or consciousness or something that they don't have yet right so it's not i think our ability to anthropomorphize those robots is probably um we're assuming that they have a level of intelligence that they don't yet have and that might be part of the fear so in that sense it's too hard but um you know there are many scary things in the world right so i think we're right to ask those questions we're right to um think about the implications of our work right in the in this in the short term as we're working on it for sure is there something long-term that scares you about our future with ai and robots a lot of folks from elon musk to sam harris to a lot of folks talk about the you know existential threats about artificial intelligence oftentimes robots kind of um inspire that the most because of the anthropomorphism do you have any fears it's an important question um i actually i think i like rod brooks answer maybe the best on this i think and it's not the only answer he's given over the years but maybe one of my favorites is he says it's not going to be he's got a book flesh and machines i believe it's not going to be the robots versus the people we're all going to be robot people because you know we already have smartphones some of us have um serious technology implanted in our bodies already whether we have a hearing aid or a pacemaker or anything like this um people with amputations might have prosthetics that's a trend i think that is likely to continue i mean this is now uh wild speculation but uh i mean when do we get to cognitive implants and the like and yeah with neurolink brain computer interfaces that's interesting so there's a there's a dance between humans and robots it's going to be it's going to be impossible to be scared of the other out there the robot because the robot will be part of us essentially it'd be so intricately sort of part of our society that and it might not even be implanted part of us but just it's so much a part of our yeah our society so in that sense the smartphone is already the robot we should be afraid of yeah uh i mean yeah and all the usual fears arise of the misinformation the manipulation all those kinds of things that um that the problems are all the same they're all they're human problems essentially it feels like yeah i mean i think the the way we interact with each other online is changing the value we put on you know personal interaction and that's a crazy big change that's going to happen and rip through our system has already been ripping through our society right and that has implications that are massive i don't know if they should be scared of it or go with the flow but i don't see you know some battle lines between humans and robots being the first thing to worry about i mean i do want to just as a kind of comment maybe you can comment about your just feelings about boston dynamics in general but you know i love science i love engineering i think there's so many beautiful ideas in it and when i look at boston dynamics or legged robots in general i think they inspire people curiosity and feelings in general excitement about engineering more than almost anything else in popular culture and i think that's such an exciting plus like responsibility and possibility for robotics and boston dynamics is riding that wave pretty damn well like they've found it they've discovered that hunger and curiosity in the people and they're doing magic with it i don't care if the i mean i guess their company have to make money right but uh they're already doing incredible work and inspiring the world about technology i mean do you have do you have thoughts about boston dynamics maybe others your own work and robotics and inspiring the world in that way i completely agree i think boston dynamics is absolutely awesome i think i show my kids those videos you know and the best thing that happens is sometimes they've already seen them you know uh right i think i i just think it's a pinnacle of success in robotics that um is just one of the best things that's happened i absolutely completely agree one of the heartbreaking things to me is how many robotics companies fail how hard it is to make money with the robotics company like irobot like went through hell just to arrive at a roomba to figure out one product and then there's so many um home robotics companies like gebo and anki anki the cutest toy that's a great robot i thought uh went down i'm forgetting a bunch of them but a bunch of robotics rods company rethink robotics um like do you um do you have any anything hopeful to say about the possibility of making money with robots oh i think um you can't just look at the failures you can all i mean boston dynamics is a success there's lots of companies that are still doing amazingly good work in robotics i mean this is the this is the capitalist ecology or something right i think you have many companies you have many startups and they push each other forward and many of them fail and some of them get through and that's sort of the natural way of things the way of those things i don't know that is robotics really that much worse i i feel the pain that you feel too every time i read one of these i um sometimes it's friends and and i definitely wish it went better or would differently but i think it's healthy and good to have um bursts of ideas burst of activities ideas if they are really aggressive they should fail sometimes certainly that's the research mantra right if you're succeeding at every problem you attempt then you're not choosing aggressively enough is it exciting to you uh the new spot oh it's okay it's so good what are you getting him as a pet uh it yeah i mean i have to dig up 75k right now it's so cool that there's a price tag you can go and and then actually buy it and i have a skydio r1 uh love it so um no i would i would i would absolutely be a customer uh i wonder what your kids would think about i i actually um zach from boston dynamics would let my kid drive in one of their demos one time and uh that was just so good so good and again forever be grateful for that and there's something magical about the anthropomorphization of that arm it adds another level of human connection i'm not sure we understand from a control aspect uh the value of anthropomorphization um i i think that's an understudied and understood engineering problem there's been a psycho psychologists have been studying it i think it's part like manipulating our mind to believe things uh is a valuable engineering like this is another degree of freedom that can be controlled i like that yeah i think that's right i think you know there's something that humans seem to do or maybe my dangerous introspection is uh i think we are able to make very simple models that assume a lot about the world very quickly and then uh it takes us a lot more time like you're wrestling you know you probably thought you knew what you're doing with wrestling and you were fairly functional as a complete wrestler and then you slowly got more expertise so maybe it's natural that our first first level of defense against seeing a new robot is to think of it in our existing models of how humans and animals behave and it's just as you spend more time with it then you'll develop more sophisticated models that will appreciate the differences exactly can you say what does it take to control a robot like what is the control problem of a robot and in general what is a robot in your view like how do you think of this system what is a robot what is a robot i think robotics ridiculous questions no no it's good um i mean there's standard definitions of combining computation with some ability to do mechanical work i think that gets us pretty close but i think robotics has this problem that once things really work we don't call them robots anymore like your my dishwasher at home is pretty sophisticated beautiful mechanisms there's actually a pretty good computer probably a couple chips in there doing amazing things we don't think of that as a robot anymore which isn't fair because then what roughly it means that robots robotics always has to solve the next problem and doesn't get to celebrate its past successes i mean even factory room floor robots are super successful they're amazing but that's not the ones i mean people think of them as robots but they don't if you ask what are the successes of robotics somehow it doesn't come to your mind immediately so the definition of robot is a system with some level automation that fails frequently something like it's it's the computation plus mechanical work and unsolved problems solve problem yeah so so from a perspective of control and mechanics dynamics what what is a robot so there are many different types of robots the control that you need for a um a jibo robot you know some some robot that's sitting on your countertop and and interacting with you but not touching you for instance is very different than what you need for an autonomous car or an autonomous drone it's very different than what you need for a robot that's going to walk or pick things up with its hands right my passion has always been for them places where you're interacting more you're doing more dynamic interactions with the world so walking now manipulation and the control problems there are are beautiful i think contact is one thing that differentiates them from many of the control problems we've solved classically right like modern control grew up stabilizing fighter jets that were passively unstable and there's like amazing success stories from control all over the place um power grid i mean there's all kinds of it's it's it's everywhere uh that we don't even realize just like ai is now so you mentioned contact like what's contact so an airplane is of extremely complex system or a spacecraft landing or whatever but at least it has the luxury of things change relatively continuously that's an oversimplification but if i make a small change in the command i send to my actuator then the path that the robot will take tends to take a change only by a small amount and there's a feedback mechanism here there's a feedback mechanism and thinking about this as locally like a linear system for instance i can use more linear algebra tools to study systems like that generalizations of linear algebra to to these smooth systems what is contact the robot has something very discontinuous that happens when it makes or breaks when it starts touching the world and even the way it touches or the order of contacts can change the outcome in potentially unpredictable ways not unpredictable but complex ways i do think there's a little bit of people a lot of people will say that contact is hard in robotics even to simulate um and i think there's a little bit of a there's truth to that but but maybe a misunderstanding around that so what is limiting is that when we think about our robots when we write our simulators we often make an assumption that that objects are rigid and when it comes down you know that they that their mass moves all you know it stays in a constant position relative to each other itself um and and that leads to some paradoxes when you go to try to talk about rigid body mechanics and contact and so for instance if i have a three-legged stool with just a imagine it comes to a point at the at the leg so it's only touching the world at a point if i draw my physics my high school physics diagram of this system then there's a couple of things that i'm given by by elementary physics i know if the system if the table is at rest if it's not moving it's zero velocities that means that the normal force all the forces are in balance so the the force of gravity is being countered by the forces that the ground is pushing on my table legs i also know since it's not rotating that there that the moments have to balance and since it can in it's a three-dimensional table it could fall in any direction it actually tells me uniquely what those three normal forces have to be if i have four legs on my table four-legged table and they were perfectly machined to be exactly the right same height and they're set down and the table's not moving then the basic conservation laws don't tell me there are many solutions for the forces that the ground could be putting on my legs that would still result result in the table not moving now the reason that seems fine i could just pick one but it gets funny now because if you think about friction we what we think about with friction is we our standard model says the amount of force that your that the table will push back if i were to now try to push my table sideways i guess i have a table here is proportional to the normal force so if i have if i'm very barely touching and i push i'll slide but if i'm pushing more and i push i'll slide less it's called coulomb friction is our standard model now if you don't know what the normal force is on the four legs and you push the table then you don't know what the friction forces are going to be right and so you can't actually tell the laws just don't aren't explicit yet about which way the table is going to go it could veer off to the left it could veer off to the right it could go straight so the rigid body assumption of contact leaves us with some paradoxes which are annoying for for writing simulators and for writing controllers we still do that sometimes because soft contact is potentially harder numerically or whatever and the best simulators do both or do some combination of the two but but anyways because of these kind of paradoxes there's all kinds of paradoxes in contact uh mostly due to these rigid body assumptions it becomes very hard to like write the same kind of control laws that we've been able to be successful with for like fighter jets we haven't been as successful writing those controllers for manipulation and so you don't know what's going to happen at the point of contact at the moment of contact there are situations absolutely where you where our laws don't tell us so the standard approach that's okay i mean instead of having a differential equation you end up with a differential inclusion it's called it's a set valued equation it says that i'm in this configuration i have these forces applied on me um and there's there's a set of things that could happen right and um and those aren't continuously i mean what uh so when you're seeing like non-smooth they're not only not smooth but this is discontinuous the non-smooth comes in when i make or break a new contact first or when i transition from stick to slip so you typically have static friction and then you'll start sliding and that'll be a discontinuous change in in velocity for instance especially if you come to rest or that's so fascinating okay so uh so what do you what do you uh do sorry i interrupted you um what's the hope under so much uncertainty about what's going to happen what are you supposed to do i mean control has an answer for this robust control is one approach but but roughly you can write controllers which try to still perform the right task despite all the things that could possibly happen the world might want the table to go this way in this way but if i write a controller that pushes a little bit more and pushes a little bit i can certainly make the table go in the direction i want it just puts a little bit more of a burden on the control system right and this discontinuities do change the control system because um the way we write it down right now every different control con configuration including sticking or sliding or parts of my body that are in contact or not looks like a different system and i think of them i reason about them separately or differently and the combinatorics of that blow up right so i just don't have enough time to compute all the possible contact configurations of my humanoid interestingly i i mean i'm a humanoid i have lots of degrees of freedom lots of joints i only i've only been around for a handful of years it's getting up there but i haven't had time in my life to visit all of the states in my system certainly all the contact configurations so if step one is to consider every possible contact configuration that i've i'll ever be in that's probably a that's probably not a problem i need to solve right just as a small attention what's a contact configuration what like just so we can uh yeah enumerate what are we talking about yeah how many are there the simplest example maybe would be imagine a robot with a flat foot and we think about the phases of gate where the heel strikes and then the four the front toe strikes and then you can heal up toe off those are each different contact configurations i only had two different contacts but i ended up with four different contact configurations now of course i might have my my robot might actually have bumps on it or other things so it could be much more subtle than that right but it's just even with one sort of box interacting with the ground already in in the plane has that many right and if i was just even a 3d foot then probably my left toe might touch just before my right toe and things get subtle now if i'm a dexterous hand and i go to talk about just grabbing a water bottle if every if i have to enumerate every possible order that my hand came into contact with the with the bottle then i'm dead in the water my any approach that we were able to get away with that in walking because we mostly touch the ground within a small number of points for instance and we haven't been able to get dextrous hands that way so i mean you've mentioned that people think that contact is really hard and that that's the reason that robotic manipulation is problem is really hard is there any flaws in that thinking so i think simulating contact is one aspect i know people often say that we don't that one of the reasons that we have a limit in robotics is because we do not simulate contact accurately in our simulators and i think that is the extent to which that's true is partly because our simulators we haven't got mature enough simulators there are some things that are still hard difficult that has changed but but we actually we know what the governing equations are they have some foibles like this indeterminacy but we should be able to simulate them accurately we have incredible open source community in robotics but it actually just takes a professional engineering team a lot of work to write a very good simulator like that uh now where does um i believe you've written drake there's a team of people i certainly spend a lot of hours on it myself well what is drake and what um what does it take to to to create a simulation environment uh for for the kind of difficult control problems we're talking about right so drake is the simulator that that i've been working on um there are other good simulators out there i don't like to think of drake as just a simulator because because we write our controllers in drake we write our perception systems a little bit in drake but we write all of our our you know low level control and even planning and uh optimization intelligence optimization capabilities absolutely yeah i mean drake is three things roughly it's an optimization library which is um sits on it it provides a layer of abstraction in c plus and python for commercial solvers you can write linear programs quadratic programs you know semi-definite programs sums of squares programs the ones we've used mixed integer programs and it will do the work to curate those and send them to whatever the right solver is for instance and it provides a level of abstraction the second thing is is a system modeling language a bit like labview or simulink where you can make block diagrams out of complex systems or it's like ross in that sense where you might have lots of ross nodes that are each doing some part of your system but to contrast it with ross we try to write if you write a drake system then you have to it asks you to describe a little bit more about the system if you have any state for instance in the system there any variables that are going to persist you have to declare them parameters can be declared and the like but the advantage of doing that is that you can if you like run things all on one process but you can also do control design against it you can do i mean simple things like rewinding and playing back your your your simulations for instance you know these things you get some rewards for spending a little bit more upfront cost in describing each system and and i i was inspired to do that because i think the complexity of atlas for instance um is just so great and i think although i mean ross has been incredible absolutely huge fan of what it's done for the robotics community but it um the ability to rapidly put different pieces together and have a functioning thing is very good but i do think that it's hard to think clearly about a bag of disparate parts mr potato head kind of software stack and if you can you know ask a little bit more out of each of those parts then you can understand the way they work better you can try to verify them and the like um you can do learning against them and then one of those systems the last thing i i said the first two things that drake is but the last thing is that there is a set of multi-body equations rigid body equations that is trying to provide a system that simulates physics and that um we also have renderers and other things but i think the physics component of drake is is special in the sense that um we have done excessive amount of engineering to to make sure that we've written the equations correctly every possible tumbling satellite or spinning top or anything that we could possibly write as a test is tested um we are making some you know i think fundamental improvements on the way you simulate contact yes what does it take to uh simulate contact i mean it just seems uh i mean there's something just beautiful the way you were like explaining contact and you're like tapping your fingers on the on the table while you're while you're doing it just um easily right easily just like just not even like it was like helping you think i guess um what i um see you have this like awesome demo of um loading or unloading a dishwasher just picking up a plate uh grasping it like for the first time um that's just seems like so difficult what how do you simulate any of that so it was really interesting that what happened was that um we started getting more professional about our software development during the darpa robotics challenge i learned the value of software engineering and how these how to bridle complexity i guess that's that's what i i want to somehow fight against and bring some of the clear thinking of controls into these complex systems we're building for robots um shortly after the darpa robotics challenge toyota opened a research institute tri toyota research institute um they put one of their there's there's three locations one of them is just down the street from mit and uh and i helped ramp that up uh right out as a part of my uh the end of my sabbatical i guess um so so tri is uh has given me the tri robotics effort has made this investment in simulation in drake and michael sherman leads a team there of just absolutely top notch dynamics experts that are trying to write those simulators that can pick up the dishes and there's also a team working on manipulation there that is taking problems like loading the dishwasher and we're using that to study these really hard corner cases kind of problems in manipulation so for me this you know simulating the dishes we could actually write a controller if we just cared about picking up dishes in the sink once we could write a controller without any simulation whatsoever and we could call it done but we want to understand like what is the path you take to actually get to a robot that could perform that for any dish uh in anybody's kitchen with with enough confidence that it could be a commercial product right and and it has deep learning perception in the loop it has complex dynamics in the loop it has controller it has a planner and how do you take all of that complexity and put it through this engineering discipline and verification and validation process to actually get enough confidence to deploy i mean the darpa challenge made me realize that that's not something you throw over the fence and hope that somebody will harden it for you that there are really fundamental challenges in uh in closing that last gap they're doing the validation and the testing i think it might even change the way we have to think about the way we write systems what happens if you if you have the robot running lots of tests it and it screws up it breaks a dish right how do you capture that i said you can't run the same simulation or the same experiment twice in in a real on a real robot do we have to be able to bring that one off exp failure back into simulation in order to change our controllers study it make sure it won't happen again do we is it enough to just try to add that to our distribution and understand that on average we're going to cover that situation again there's like really subtle questions at the corner cases that i think we don't yet have satisfying answers for like how do you find the corner cases that's one kind of is there do you think this possible to create a systematized way of discovering corner cases efficiently yeah in whatever the problem is yes i mean i think we have to get better at that i mean control theory has um for for decades talked about active experiment design so people call it curiosity these days it's roughly this idea of trying to exploration or exploitation but but in the active experiment design is even is is more specific you could try to understand the uncertainty in your system design the experiment that will provide the maximum information to reduce that uncertainty if there's a parameter you want to learn about what is the optimal trajectory i could execute to learn about that parameter for instance scaling that up to something that has a deep network in the loop and the planning in the loop is tough we've done some work on you know with matt o'kelly and amancina we have we've worked on um some falsification algorithms that are trying to do rare event simulation that try to just hammer on your simulator and if your simulator is good enough you can um you can spend a lot of time or you can write good algorithms that try to spend most of their time in the corner cases so you basically imagine you're you're building an autonomous car and you want to put it in i don't know downtown new delhi all the time right an accelerated testing if you can write sampling strategies which figure out where your controller is performing badly in simulation and start generating lots of examples around that you know it's just the space of possible places where that can be where things can go wrong is very big so it's hard to write those algorithms yeah rare event simulation is just like a really compelling notion uh if it's possible we joked and we called we call it the black swan generator it's a black swan right because you don't just want the rare events you want the ones that are highly impactful i mean that's the most those are the most sort of profound questions we ask of our world like uh what's the uh what's the worst that can happen uh but what we're really asking isn't some kind of like computer science worst case analysis we're asking like what are the millions of ways this can go wrong and that's like our curiosity we humans i think are pretty bad at uh we just like run into it and i think there's a distributed sense because there's now like 7.5 billion of us and so there's a lot of them and then a lot of them write blog posts about the stupid thing they've done so we learn in a distributed way um there's there's something that's going to be important for robots too yeah i mean that's that's another massive theme at toyota research for robotics is this fleet learning concept is um you know the idea that i as a humanoid don't have enough time to visit all of my states right there's just a it's very hard for one robot to experience all the things but that's not actually the problem we have to solve right um we're gonna have fleets of robots that can have very similar appendages and at some point maybe collectively they have enough data that their computational processes should be set up differently than ours right it's a have this vision of just i mean all these uh dishwasher unloading robots i mean um that robot dropping a plate and a human looking at the robot probably pissed off yeah but uh that's a special moment to record i think one one thing in terms of fleet learning and i've seen that because i i've talked to a lot of folks um just like like tesla users or tesla drivers they're not another another company that's using this kind of fleet learning idea and one hopeful thing i have about humans is they really enjoy when a system improves learns so they enjoy fleet learning and they're the reason it's hopeful for me is they're willing to put up with something that's kind of dumb right now and they're like if it's improving they almost like enjoy being part of the like teaching it almost like we if you have kids like you're teaching them something right um i think that's a beautiful thing because that that gives me hope that we can put dumb robots out there uh as long i mean the problem with on the tesla side with cars cars can kill you that's that makes the problem so much harder dishwasher unloading is a little safe that's why home robotics is uh it's really exciting and just to clarify i mean for people who might not know a tri toyota research institute so they're uh i mean they're they're pretty well known for like autonomous vehicle research but they're also interested in in home robotics yep there's a big there's a big group working on multiple groups working on home robotics it's a major part of the portfolio also there's also a couple other projects an advanced materials discovery i'm using ai and machine learning to discover new materials for um for car batteries and then the like for instance yeah and that's been actually an incredibly successful team uh there's new projects starting up too so do you see a future of uh where like robots are in our home and and like robots that have like um actuators that look like arms in our home or like you know more like humanoid type robots or is this are we gonna is we're gonna do the same thing that you just mentioned that you know the dishwasher is no longer a robot we're going to just not even see them as robots but do i mean what's your vision of the home of the future 10 20 years from now 50 years if you get crazy yeah i think we already have roombas cruising around we have uh uh you know alexa's or google homes on their our kitchen counter it's only a matter of time till they spring arms and start doing something useful like that um so i do think it's coming i think it's lots of people have lots of motivations for doing it it's been super interesting actually learning about toyota's vision for it which is about helping people age in place because i think that's not necessarily the first entry the most lucrative entry point but it's the problem maybe that we really need to solve no matter what and so i think i think there's a real opportunity it's a delicate problem how do you work with people help people keep them active engaged you know but improve their quality of life and uh and and help them age in place for instance it's interesting because older folks are also i mean there's a contrast there because um they're not always the the folks who are the most comfortable technology for example so there's a there's a there's a division that's interesting there that you can do so much good with a robot for for older folks but there's a there's a gap to feel of understanding i mean it's actually kind of beautiful um robot is learning about the human and the human is kind of learning about this new robot thing and it's uh also with um at least with uh like when i talk to my parents about robots there's a little bit of a blank slate there too like you can i mean they don't know anything about robotics so it's completely like wide open they don't have that they haven't my parents haven't seen black mirror so like they they there's it's a blank slate here's a cool thing like what can you do for me yeah so it's an exciting space i think it's a really important space i do feel like you know a few years ago uh drones were successful enough in academia they kind of broke out and started in industry and autonomous cars have been happening it does feel like manipulation in logistics of course first but in the home shortly after seems like one of the next big things that's going to really pop so uh i don't think we talked about it but uh what's soft robotics so we talked about like rigid bodies like if we can just linger on this whole touch thing um yeah so what's soft robotics so i told you that i really dislike the fact that robots are afraid of touching the world all over their body so there's a couple reasons for that if you look carefully at all the places that robots actually do touch the world they're almost always soft they have some sort of pad on their fingers or a rubber sole on their foot but if you look up and down the arm we're just pure aluminum or something so uh so that makes it hard actually in fact hitting the table with your you know your rigid arm or nearly rigid arm is a is a has some of the problems that we talked about in terms of simulation i think it it fundamentally changes the mechanics of contact when you're soft right you you turn point contacts into patch contacts which can have torsional friction you can have um distributed load if i want to pick up an egg right if i pick it up with two points then in order to put enough force to sustain the weight of the egg i might have to put a lot of force to break the egg if i envelop it with a with contact all all around then i can distribute my force across the shell of the egg and have a better chance of not breaking it so soft robotics is for me a lot about changing the mechanics of contact does it make the problem a lot harder um quite the opposite uh it it changes the computational problem i think because of the i think our world and our mathematics has biased us towards ridgid but it really should make things better in some ways right um it's it's a i think the the the future is unwritten there um but the other thing is ultimately sorry to interrupt they think ultimately it will make things simpler if we embrace the softness of the world it makes um it makes things smoother right so the the result of small actions is less discontinuous but it also means potentially less you know instantaneously bad for instance i won't necessarily contact something and send it flying off the other aspect of it that just happens to dovetail really well is that if soft robotics tends to be a place where we can embed a lot of sensors to so if you change your your hardware and make it more soft then you can potentially have a tactile sensor which is measuring the deformation so there's a team at tri that's working on soft hands and and you get so much more information if you you can put a camera behind the skin roughly and and get fantastic tactile information which is um it's super important like in manipulation one of the things that really is frustrating is if you work super hard on your head mounted on your perception system for your head mounted cameras and then you've identified an object you reach down to touch it and the first the last thing that happens right before the most important time you stick your hand and you're occluding your head mounted sensors right so in all the part that really matters all of your off board sensors are you know are occluded and really if you don't have tactile information then you're you're blind in an important way so it happens that soft robotics and tactile sensing tend to go hand in hand i think we've kind of talked about it but uh you taught a course on under actuator robotics i believe that was the name of it actually that's right can you talk about it in that context what is under actuated robotics right so under-actuated robotics is my graduate course it's it's online mostly now so i mean in the sense that the lecturer's versions of it i think right the youtube really great i recommend it highly look on youtube for the 2020 versions until march and then you have to go back to 2019 thanks to covet um no i've poured my heart into that class and lecture one is basically explaining what the word underactuated means so people are very kind to show up and then maybe have to learn what the title of the course means over the course of the first lecture that that first lecture is really good you should watch it it's it's a strange name but um i thought it captured the essence of what control was good at doing and what control was bad at doing so what do i mean by under actuated so a mechanical system has many degrees of freedom for instance i think of a joint as a degree of freedom and it has some number of actuators motors so if you have a robot that's bolted to the table that has five degrees of freedom and five motors then you have a fully actuated robot if you have if you take away one of those motors then you have an under actuated robot now why on earth i i have a good friend who who likes to tease me he said russ if you had more research funding would you work on fully actuated robots yeah and uh the answer is no the world gives us under-actuated robots whether we like it or not i'm a human i'm an under actuated robot even though i have more muscles than my big degrees of freedom because i have in some places multiple muscles attached to the same joint but still there's a really important degree of freedom that i have which is the location of my center of mass in space for instance all right i'm i can jump into the air and there's no motor that connects my center of mass to the ground in that case so i have to think about these the implications of not having control over everything the passive dynamic walkers are the extreme view of that where you've taken away all the motors and you have to let physics do the work but it shows up in all the walking robots where you have to use some of the actuators to push and pull even the degrees of freedom that you don't have an actuator on that's referring to walking if you're like falling forward like is there a way to walk that's fully actuated so it's a subtle point when you're when you're in contact and you have your feet on the ground there are still limits to what you can do right unless i have suction cups on my feet i cannot accelerate my center of mass towards the ground faster than gravity because i can't get a force pushing me down right but i can still do most of the things that i want to so you can get away with basically thinking of the system as fully actuated unless you suddenly need it to accelerate down super fast but as soon as i take a step i i get into more nuanced territory and to get to really dynamic robots or airplanes or other things i think you have to embrace the under actuated dynamics manipulation people think is manipulation under under actuated my even if my arm is fully actuated i have a motor if my goal is to control the position and orientation of this cup then i don't have an actuator for that directly so i have to use my actuators over here to control this thing now it gets even worse like what if i have to button my shirt okay what are the degrees of freedom of my shirt right i suddenly that's a hard question to think about it kind of makes me queasy as a thinking about my state-space control ideas but actually those are the problems that make me so excited about manipulation right now is that it it breaks some of the it breaks a lot of the foundational control stuff that i've been thinking about is there um what are some interesting insights you could say about trying to solve an under actuated like control in in an underactuated system so i think the philosophy there is let physics do more of the work the technical approach has been optimization so you typically formulate your decision making for control as an optimization problem and you use the language of optimal control and sometimes numero often numerical optimal control in order to make those decisions and balance you know these complicated equations of and in order to control you don't have to use optimal control to do under-actuated systems but that has been the technical approach that has borne the most fruit in our at least in our line of work and there's some so in under actuator systems when you say let physics do some of the work so there's a kind of feedback feedback loop that observes the state that the physics brought you to so like you've there's a there's a perception there this is there's a feedback somehow do you do um do you ever loop in like complicated perception systems into this whole picture right right around the time of the darpa challenge we had a complicated perception system in the darpa challenge we also started to embrace perception for our flying vehicles at the time we had a a really good project on trying to make airplanes fly at high speeds through forests um sirtex caramel was on that project and it was a really fun team to to work on he's carried it farther much farther forward since then so that's using cameras for perception so that was using cameras uh that was a at the time we felt like lidar was too too heavy and two power heavy to to be carried on on a light uav and we were using cameras and that was a big part of it was just how do you do even stereo matching at a fast enough rate with a small camera a small onboard compute since then we have now the so the deep learning revolution unquestionably changed what we can do with perception for robotics and control so in manipulation we can address we can use perception in a i think a much deeper way and um we get into not only i think the the first use of it naturally would be to ask your deep learning system to look at the cameras and produce the state which is like the pose of my thing for instance but i think we've quickly found out that that's not always the right thing to do um why is that because what's the state of my shirt imagine i've always very noisy i mean or it's um if the first step of me trying to button my shirt is estimate the full state of my shirt including like what's happening in the backyard or whatever whatever that's just not the right specification there are aspects of the state that are very important to the task there are many that are unobservable and not not important to the task so you really need it begs new questions about state representation another example that we've been playing with in lab has been just the idea of chopping onions okay or carrots turns out to be better so the onions stink up the lab uh and they're hard to see in a camera but uh so details matter yeah details matter you know so um moving around a particular object right then i think about oh it's got a position or an orientation in space that's the description i want now when i'm chopping an onion okay the first chop comes down i have now a hundred pieces of onion does my control system really need to understand the position and orientation and even the shape of the hundred pieces of onion in order to make a decision probably not you know and like if i keep going i'm just getting more and more is my state space getting bigger as i cut it's it um it it's not right yes so there's a i think there's a richer uh idea of state it's not the state that is given to us by lagrangian mechanics there is a there is a proper lagrangian state of the system but the relevant state for this is some latent state is what we call it in machine learning but you know there's some some different state representatives some compressed representation some and that's what i i worry about saying compressed because it doesn't i don't mind that it's low dimensional or not but it has to be something that's easier to think about by us humans or my algorithms or the algorithms being like control optimal so for instance if the contact mechanics of all of those onion pieces and all the permutations of possible touches between those onion pieces you know you can give me a high dimensional state representation i'm okay if it's linear but if i have to think about all the possible shattering combinatorics of that then my robot is going to sit there thinking and uh the soup's gonna get cold or something so um since you taught the course i've it kind of entered my mind um the idea of under actuated as really compelling to see the to see the world in this kind of way um do you ever you know if we talk about onions or you talk about the world with people in it in general do you see the world as a basically an underactuated system do you like often look at the world in this way or is this uh overreach um under actuated as a way of life man exactly um i guess that's what i'm asking i do think it's everywhere i think some in some places um we already have natural tools to deal with it you know it rears its head i mean in linear systems it's not a problem we just we just like an under actuated linear system is really not sufficiently distinct from a fully actuated linear system it's it's a it's a subtle point about when that becomes a bottleneck and what we know how to do with control it happens to be a bottleneck although we've gotten incredibly good solutions now but for a long time that i felt that that was the key bottleneck in legged robots and roughly now the under actuated course is you know me trying to tell people everything i can about how to make atlas do a backflip right i have a second course now in that i teach in the other semesters which is on on manipulation and that's where we get into now more of the that's a newer class i'm hoping to put it online this fall completely and uh that's going to have much more aspects about these perception problems and the state representation questions and then how do you do control and the the thing that's a little bit sad is that uh for me at least is there's a lot of manipulation tasks that people want to do and should want to do they could start a company with it and make very successful that don't actually require you to think that much about under or dynamics at all even but certainly under actuated dynamics once i have if i if i reach out and grab something if it if i can sort of assume it's rigidly attached to my hand then i can do a lot of interesting meaningful things with it without really ever thinking about the dynamics of that object so they built we've built systems that kind of reduced the need for that enveloping grasps and the like um but i think the really good problems in manipulation so manipulation by the way is more than just pick and place that's like a lot of people think of that just grasping i don't mean that i mean buttoning my shirt i mean tying shoe laces how do you program a robot to tie shoelaces and not just one shoe but every shoe right that's a really good problem it's tempting to write down like the infinite dimensional state of the of the laces that's probably not needed to write a good controller i know we could hand design a controller that would do it but i don't want that i want to understand the principles that would allow me to solve another problem that's kind of like that but i think if we can stay pure in our approach then the challenge of tying anybody's shoes is a great challenge that's a great challenge i mean and the soft touch comes into play there that's really interesting let me ask another ridiculous question on this topic um how important is touch we haven't talked much about humans but i have this argument with my dad where like i think you can fall in love with the robot based on uh language alone and he believes that touch is essential i touch and smell he says but um so in terms of robots you know connecting with humans and uh we can go philosophical in terms of like a deep meaningful connection like love but even just like collaborating in an interesting way how important is touch like uh from the engineering perspective and the philosophical one i think it's super important let's even just in a practical sense if we forget about the emotional part of it but for robots to interact safely while they're doing meaningful mechanical work in the pro in the you know close contact with or vicinity of people that need help i think we have to have them they have we have to build them differently um they have to be afraid not afraid of touching the world so uh i think baymax is just awesome that's just like the the the movie of big hero 6 and the the concept of baymax that's just awesome i think we should and we have some folks at toyota that are trying to toyota research that are trying to build baymax roughly and i think it's just a fantastically good project i think it will change the way people physically interact the same way i mean you gave a couple examples earlier but but if i um if the robot that was walking around my home looks more like a teddy bear and a little less like the terminator that could change completely the way people perceive it and interact with it and maybe they'll even want to teach it like you said right you could um not quite gamify it but somehow instead of people judging it and looking at it as if uh it's not doing as well as a human they're going to try to help out the cute teddy bear right who knows but i i think we're building robots wrong and being more soft and more contact is important right yeah and like all the magical moments i can remember with robots well first of all just visiting your lab seeing atlas but also spot menu when i first spot saw spot many in person and hung out with him her uh it i don't have trouble engendering robots i feel robotics people really say always it i kind of like the idea that it's a her or him uh there's a magical moment but there's no touching uh i guess the question i have have you ever been um like have you had a human robot experience where like a robot touched you and like it was like wait like was there a moment that you've forgotten that a robot is a robot and like the anthropomorphization stepped in and for a second you forgot that it's not human i mean i think when you're in on the details then we we of course anthropomorphized our work with atlas but in you know in verbal communication and the like i think we were pretty aware of it as a machine that needed to be respected um i actually i worry more about the smaller robots that could still you know move quickly if programmed wrong and uh and we have to be careful actually about safety and the like right now and that if we build our robots correctly i think then those a lot of those concerns could go away and we're seeing that trend we're seeing the lower cost lighter weight arms now that could be fundamentally safe um i mean i do think touch is so fundamental ted adelson is uh is great he's a perceptual scientist at mit and he studied vision most of his life and he said when i had kids i expected to be fascinated by their perceptual development but what really what he noticed was felt more impressive more dominant was the way that they would touch everything and lick everything and pick things up stick it on their tongue and whatever and he said watching his daughter uh convinced him that actually he needed to study tactile sensing more so there's something very important i think it's a little bit also of the passive versus active part of the world right you can passively perceive the world but it's fundamentally different if you can do an experiment right and if you can change the world and you can learn a lot more than a passive observer so you can in dialogue that was your initial example you could have an active experiment exchange but i think if you're just a camera watching youtube i think that's a very different problem than if you're a robot that can apply force and touch i i i think it's important yeah i think it's just an exciting area of research i think you're probably right that this hasn't been under researched it's uh to me as a person who's captivated by the idea of human robot interaction it feels like such a rich opportunity to explore touch not even from a safety perspective but like you said the emotional too i mean safety comes first um but the next step is like you know uh like a real human connection even in the war like even in the industrial setting it just feels like uh it's nice for the robot i don't know i you know you might disagree with this but um because i think it's important to see robots as tools often but i don't know i think they're just always going to be more effective once you humanize them uh like it's convenient now to think of them as tools because we want to focus on the safety but i think ultimately to create like a good experience for the worker for the person there has to be a human element i don't know for me i i it feels like like an industrial robotic arm would be better if as a human element i think like we think robotics had that idea with baxter and having eyes and so on having i don't know i'm a big believer in that i it's not my area but i am also a big believer do you have an emotional connection to atlas like yeah do you miss him i mean yes i i i don't know if i'd more so than if i had a different science project that i'd worked on super hard right but uh um yeah i mean the robot we basically had to do heart surgery on the robot in the final competition because we melted the core um and uh and yeah there was something about watching that robot hanging there we know we had to compete with it in an hour and it was getting its guts ripped out those are all historic moments i think if we look back like 100 years from now um yeah i think those are important moments in robotics i mean these are the early day you look at like the early days of a lot of scientific disciplines they look ridiculous they're full of failure but it feels like robotics will be important in the coming uh 100 years and these are the early days so so i think a lot of people are look at uh a brilliant person such as yourself and and are curious about the intellectual journey they've took um is there maybe three books technical fiction philosophical that um had a big impact on your life that you would recommend perhaps others reading yeah so um i actually didn't read that much as a kid but i read fairly voraciously now um there are some recent books that if you're interested in this kind of topic like ai superpowers by kaifuli is just a fantastic read you must read that um yuval harari is just i think that can open your mind um sapiens sapiens as as the first one homo deuce is the second yeah i think we mentioned the black swan by taleb i think that's a good sort of mind opener i actually um so so there's maybe a more controversial recommendation i could give um great well i would love something sure in some sense it's it's so classical it might surprise you but i actually recently read um mortimer adler's how to read a book not so long it was a while ago but some people hate that book i loved it i think we're in this time right now where um boy we're just inundated with research papers that you could read on archive with limited peer review and just this wealth of information um i don't know i think the passion of um what you can get out of a book a really good book or a really good paper if you find it the attitude the realization that you're only going to find a few that really are worth all your time but then once you find them you should just dig in and and and understand it very deeply and it's worth you know marking it up and and uh you know having the hard copy writing in the the side notes side margins um i think that was really it i read it at the right time where i was just feeling just overwhelmed with really low quality stuff i guess and similarly uh i'm just giving more than three now i'm sorry if i've exceeded my my quota but on that topic just real quick is uh so basically finding a few companions to keep for the rest of your life in terms of papers and books and so on and those are the ones like not doing um what is it fomo fear missing out constantly trying to update yourself but really deeply making a life journey of studying a particular paper essentially a set of papers yeah i think when you really find something which a book that resonates with you might not be the same book that resonates with me but um when you really find one that resonates with you i think the dialogue that happens and that's what i love that adler was saying you know i think socrates and plato say um the the written word is never going to capture the beauty of dialogue right but adler says no no um a a really good book is a dialogue between you and the author and it crosses time and space and uh i don't know i think it's a very romantic there's a bunch of like specific advice which you can just gloss over but the romantic view of how to read and really appreciate it is is is so good and similarly teaching i uh um i thought a lot about teaching and uh and so isaac asimov great science fiction writer has also actually spent a lot of his career writing nonfiction right his memoir is fantastic he was passionate about explaining things right he wrote all kinds of books on all kinds of topics in science he was known as the great explainer and some you know i i do really resonate with his style and uh and just his way of talking about you know by communicating and explaining to something is really the way that you learn something i think i think about problems very differently because of the way i've been given the opportunity to teach them at mit and we have questions asked you know the fear of the lecture the experience of the lecture and the questions i get and the interactions just forces me to be rock solid on on these ideas in a way that i didn't have that i i don't know i would be in a different intellectual space also video does that scare you that your lectures are online and people like me and sweatpants can sit sipping coffee and watch what you give lectures that i think it's great i do think that something's changed right now which is you know right now we're giving lectures over zoom i mean giving seminars over zoom and everything um i'm trying to figure out i think it's a new medium do you think it's trying to figure out how to use it yeah i've been um i've been quite um cynical about the human to human connection over over that medium but i think that's because it's hasn't been explored fully and teaching is a different thing every lecture is a is a i'm sorry every seminar even i think every talk i give i i you know there's an opportunity to give that differently i can i can deliver content directly into your browser you have a webgl engine right there i could i can throw 3d uh content into your browser while you're listening to me right yeah and i can assume that you have a you know at least a powerful enough laptop or something to watch zoom while i'm doing that while i'm giving a lecture that that's a that's a new communication tool that i didn't have last year right and uh i think robotics can potentially benefit a lot from teaching that way we'll see it's going to be an experiment this fall i'm thinking a lot about it yeah and also like um the the length of lectures or the length of like um there's something so like i guarantee you you know it's like 80 percent of people who started listening to our conversation are still listening to now which is crazy to me but so there's a there's a patience and a interest in long-form content but at the same time there's a magic to forcing yourself to condense an idea to as short as possible uh as short as possible like clip it can be part of a longer thing but like just like really beautifully condensed idea there's a lot of opportunity there that's easier to do and remote with i don't know uh with editing too editing is an interesting thing like what uh you know most professors don't get when they give a lecture you don't get to go back and edit out parts like chris like crisp it up a little bit that's also it can do magic like if you remove like five to ten minutes from an hour lecture it can it can actually cr it can make something special of a lecture i've uh i've seen that in myself and and in others too because i edit other people's lectures to extract clips it's like there's certain tangents they're like that lose they're not interesting they're they're they're mumbling they're just not they're not clarifying they're not helpful at all and once you remove them it's just i don't know editing can be magic uh take a lot of time yeah it takes it depends like what is teaching you have to ask um yeah because i find the editing process is also beneficial as uh for teaching but also for your own learning i don't know if have you watched yourself in the survey have you watched those videos it's i mean not all of them okay it could be it could be painful yeah and to see like how to improve so do you find that i know you segment your um your podcast do you think that helps people with the the attention span aspect of it or is it segment like sections like yeah we're talking about this topic whatever no no that just helps me it's actually bad so uh and you've been incredible uh so i'm i'm learning like i'm afraid of conversation this is even today i'm terrified of talking to you i mean it's something i'm um trying to remove from myself i there's this a guy i mean i've learned from a lot of people but really um there's been a few people who's been inspirational to me in terms of conversation whatever people think of him joe rogan has been inspirational to me because comedians have been too being able to just have fun and enjoy themselves and lose themselves in conversation that requires you to be a great storyteller to be able to uh pull a lot of different pieces of information together but mostly just to enjoy yourself in conversations i'm trying to learn that these notes are you see me looking down that's like a safety blanket that i'm trying to let go of more and more cool so that's that people love just regular conversation that's what they the structure is like whatever i would say i would say maybe like 10 to like so there's a bunch of you know there's uh probably a couple thousand phd students listening to this right now right and they might know what we're talking about but there's somebody i guarantee you right now in russia some kid who's just like who's just smoke some weed is sitting back and just enjoying the hell out of this conversation not really understanding he kind of watched some boston dynamics videos he's just enjoying it um and i salute you sir uh no but just like there's a so much variety of people that just have curiosity about engineering about sciences about mathematics and um and also like i should that i mean uh enjoying it is one thing but i also often notice it inspires people to there's a lot of people who are like in their undergraduate studies trying to figure out what uh trying to figure out what to pursue and those these conversations can really spark the direction there of their life and in terms of robotics i hope it does because uh i'm excited about the possibilities for robotics brings on that topic um do you have advice like what advice would you give to a young person about life a young person about life or a young person about life and robotics uh it could be in robotics it could be in life in general it could be career it could be uh relationship advice it could be running advice just like they're um that's one of the things i see you like to talk to like 20 year olds they're they're like how do i how do i do this thing what do i do um if they come up to you what would you tell them i think it's an interesting time to be a kid these days everything points to this being sort of a winner take all economy and the like i think the people that will really excel in my opinion are going to be the ones that can think deeply about problems you have to be able to ask questions agilely and use the internet for everything it's good for and stuff like this and i think a lot of people will develop those skills i think the the leaders thought leaders you know robotics leaders whatever are going to be the ones that can do more and they can think very deeply and critically um and that's a harder thing to learn i think one one path to learning that is through mathematics through engineering i would encourage people to start math early i mean i didn't really start i mean i was always in the the better math classes that i could take but i wasn't pursuing super advanced mathematics or anything like that until i got to mit i think mit lit me up and really started the life that i'm living now but yeah i really want kids to to dig deep really understand things building things too i mean pull things apart put them back together like that's just such a good way to really understand things and expect it to be a long journey right it's uh you don't have to know everything you're never gonna know everything so think deeply and stick with it enjoy the ride but just make sure you're not um yeah just just make sure you're you're you're stopping to think about why things work yeah it's true it's uh it's easy to lose yourself in the in the in the distractions of the world we're overwhelmed with content right now but you have to stop and pick some of it and really understand yeah on the book point i've read animal farm by george orwell a ridiculous number of times so for me like that book i don't know if it's a good book in general but for me it connects deeply somehow uh it somehow connects so i was born in the soviet union so it connects to me to the entire history of the soviet union and to world war ii and to the love and hatred and suffering that went on there and the uh the corrupting nature of power and greed and just somehow i just that that that book has taught me more about life than like anything else even though it's just like a silly like childlike book about adam pigs it's like i don't know why it just connects and inspires uh the same there's a few um yeah there's a few technical books too and algorithms that just yeah you return too often right i'm i'm i'm with you uh yeah there's uh i don't and i've been losing that because of the internet i've been like uh going and i've been going on archive and blog posts and github and and the new thing and of um you lose your ability to really master an idea right wow exactly right what's a fond memory from childhood when baby russ tedrick well i guess i just said that um at least my current life begins began when i got to mit if i have to go farther than that yeah what was was there life before mit oh absolutely but but let me actually tell you what happened when i first got to mit because that i think might be relevant here but i yeah you know i i had taken a computer engineering degree at michigan i enjoyed it immensely learned a bunch of stuff i was i liked computers i liked how to like programming um but when i did get to mit and started working with sebastian sung theoretical physicist computational neuroscientist um the culture here was just different um it demanded more of me certainly mathematically and in the critical thinking and i remember the day that i uh borrowed one of the books from my advisor's office and walked down to the charles river and was like i'm getting my butt kicked you know um and i think that's going to happen to everybody who's doing this kind of stuff right i think uh i expected you to ask me the meaning of life you know i think that the uh um somehow i think that's that's gotta be part of it this doing hard things yeah did you uh did you consider quitting at any point did you consider this isn't for me no never that i mean i was it was working hard but i was loving it right there's i think the there's this magical thing where you you know i'm lucky to surround myself with people that basically almost every day i'll i'll i'll see something i'll be told something or something that i realize wow i don't understand that and if i could just understand that there's there's something else to learn that if i could just learn that thing i would connect another piece of the puzzle and and uh you know i think that is just such an important aspect and being willing to understand what you can and can't do and and loving the journey of going and learning those other things i think that's the best part i don't think there's a better way to end it or us i've um you've been an inspiration to me since i showed up at mit uh your work has been an inspiration to the world this conversation was amazing i can't wait to see what you do next with robotics home robots i i hope to see you work in my home one day thanks so much for talking today has been awesome cheers thanks for listening to this conversation with rasteric and thank you to our sponsors magic spoon serial betterhelp and expressvpn please consider supporting this podcast by going to magicspoon.com lex and using codelex at checkout going to betterhelp.com lex and signing up at expressvpn.com lexpod click the links buy the stuff get the discount it really is the best way to support this podcast if you enjoy this thing subscribe on youtube review it with five stars and apple podcast support on patreon or connect with me on twitter at lex friedman spelled somehow without the e just f-r-i-d-m-a-n and now let me leave you with some words from neil degrasse tyson talking about robots in space and the emphasis we humans put on human-based space exploration robots are important if i don my pure scientist hat i would say just send robots i'll stay down here and get the data but nobody's ever given a parade for a robot nobody's ever named a high school after a robot so when i down my public educator hat i have to recognize the elements of exploration that excite people it's not only the discoveries and the beautiful photos that come down from the heavens it's the vicarious participation in discovery itself thank you for listening and hope to see you next time you