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AutoPhoto: Aesthetic Photo Capture using Reinforcement Learning | https://ieeexplore.ieee.org/document/9636788/ | [
"Hadi AlZayer",
"Hubert Lin",
"Kavita Bala",
"Hadi AlZayer",
"Hubert Lin",
"Kavita Bala"
] | The process of capturing a well-composed photo is difficult and it takes years of experience to master. We propose a novel pipeline for an autonomous agent to automatically capture an aesthetic photograph by navigating within a local region in a scene. Instead of classical optimization over heuristics such as the rule-of-thirds, we adopt a data-driven aesthetics estimator to assess photo quality. ... |
Motion Strategy Using Opponent Player’s Serial Learning for Air-Hockey Robots | https://ieeexplore.ieee.org/document/9635854/ | [
"Shotaro Fukuda",
"Koichiro Tadokoro",
"Akio Namiki",
"Shotaro Fukuda",
"Koichiro Tadokoro",
"Akio Namiki"
] | In recent years, there have been many studies on sports robots that can play against humans, including studies on the strategies that sports robots use by taking into account the physical conditions of their opponents. However, there have been few studies on strategies that take into account psychological conditions of the opponents, such as carelessness and habituation. This paper proposes a moti... |
Learning Robotic Contact Juggling | https://ieeexplore.ieee.org/document/9636790/ | [
"Kazutoshi Tanaka",
"Masashi Hamaya",
"Devwrat Joshi",
"Felix von Drigalski",
"Ryo Yonetani",
"Takamitsu Matsubara",
"Yoshihisa Ijiri",
"Kazutoshi Tanaka",
"Masashi Hamaya",
"Devwrat Joshi",
"Felix von Drigalski",
"Ryo Yonetani",
"Takamitsu Matsubara",
"Yoshihisa Ijiri"
] | Robotic contact juggling is a challenging task in which robots must control the movement of a ball rapidly and indirectly without holding it while keeping the ball in and sometimes out of contact with the robot’s body. In this work, we address the problem of learning such robotic contact juggling from trial and error via model-based reinforcement learning (MBRL). The key insight is that complex ro... |
Towards a User Adaptive Assistive Robot: Learning from Demonstration Using Navigation Functions | https://ieeexplore.ieee.org/document/9636200/ | [
"Xanthi S. Papageorgiou",
"Athanasios C. Dometios",
"Costas S. Tzafestas",
"Xanthi S. Papageorgiou",
"Athanasios C. Dometios",
"Costas S. Tzafestas"
] | Elderly and mobility impaired people need special attention during bathing activities, since these tasks are demanding in body flexibility. Our aim is to build an assistive robotic bathing system, in order to increase the independence and safety of this procedure. Towards this end, the expertise of professional carers for bathing sequences and appropriate motions have to be adopted, in order to ac... |
Cross-Modal Analysis of Human Detection for Robotics: An Industrial Case Study | https://ieeexplore.ieee.org/document/9636158/ | [
"Timm Linder",
"Narunas Vaskevicius",
"Robert Schirmer",
"Kai O. Arras",
"Timm Linder",
"Narunas Vaskevicius",
"Robert Schirmer",
"Kai O. Arras"
] | Advances in sensing and learning algorithms have led to increasingly mature solutions for human detection by robots, particularly in selected use-cases such as pedestrian detection for self-driving cars or close-range person detection in consumer settings. Despite this progress, the simple question which sensor-algorithm combination is best suited for a person detection task at handƒ remains hard ... |
Consolidating Kinematic Models to Promote Coordinated Mobile Manipulations | https://ieeexplore.ieee.org/document/9636351/ | [
"Ziyuan Jiao",
"Zeyu Zhang",
"Xin Jiang",
"David Han",
"Song-Chun Zhu",
"Yixin Zhu",
"Hangxin Liu",
"Ziyuan Jiao",
"Zeyu Zhang",
"Xin Jiang",
"David Han",
"Song-Chun Zhu",
"Yixin Zhu",
"Hangxin Liu"
] | We construct a Virtual Kinematic Chain (VKC) that readily consolidates the kinematics of the mobile base, the arm, and the object to be manipulated in mobile manipulations. Accordingly, a mobile manipulation task is represented by altering the state of the constructed VKC, which can be converted to a motion planning problem, formulated and solved by trajectory optimization. This new VKC perspectiv... |
An Efficient Understandability Objective for Dynamic Optimal Control | https://ieeexplore.ieee.org/document/9636007/ | [
"D. Livingston McPherson",
"S. Shankar Sastry",
"D. Livingston McPherson",
"S. Shankar Sastry"
] | Motion optimization for legible robot intent has largely ignored the robot’s dynamics, citing burdensome complexity that prevents online deployment. Even where the original task (to be communicated) could be solved on the dynamical system, the legibility problem (to communicate that task’s intent) could not. This work simplifies the legibility objective to have equivalent computational complexity ... |
A Multimodal and Hybrid Framework for Human Navigational Intent Inference | https://ieeexplore.ieee.org/document/9635900/ | [
"Zhitian Zhang",
"Jimin Rhim",
"Angelica Lim",
"Mo Chen",
"Zhitian Zhang",
"Jimin Rhim",
"Angelica Lim",
"Mo Chen"
] | Understanding human navigational intent is essential for robots to be able to interact with and navigate around humans safely and naturally. Current methods typically perform inference through only one mode of perception such as human motion trajectory, and a single theoretical framework such as a learning-based or classical approach. In contrast, this paper studies prediction of human navigationa... |
Multi-modal Scene-compliant User Intention Estimation in Navigation | https://ieeexplore.ieee.org/document/9636142/ | [
"Kavindie Katuwandeniya",
"Stefan H. Kiss",
"Lei Shi",
"Jaime Valls Miro",
"Kavindie Katuwandeniya",
"Stefan H. Kiss",
"Lei Shi",
"Jaime Valls Miro"
] | A multi-modal framework to generate user intention distributions when operating a mobile vehicle is proposed in this work. The model learns from past observed trajectories and leverages traversability information derived from the visual surroundings to produce a set of future trajectories, suitable to be directly embedded into a perception-action shared control strategy on a mobile agent, or as a ... |
Simultaneous Prediction of Pedestrian Trajectory and Actions based on Context Information Iterative Reasoning | https://ieeexplore.ieee.org/document/9636252/ | [
"Bo Chen",
"Decai Li",
"Yuqing He",
"Bo Chen",
"Decai Li",
"Yuqing He"
] | Pedestrian trajectories and actions prediction in complex environment is challenging due to the complexity of human behavior and a variety of internal and external stimuli. Much works has gone towards predicting trajectories and actions separately without mining the coupling relationships between them, which is an important information for our humans to reason and predict. Inspired by this, we pro... |
Safety-Oriented Pedestrian Occupancy Forecasting | https://ieeexplore.ieee.org/document/9636691/ | [
"Katie Luo",
"Sergio Casas",
"Renjie Liao",
"Xinchen Yan",
"Yuwen Xiong",
"Wenyuan Zeng",
"Raquel Urtasun",
"Katie Luo",
"Sergio Casas",
"Renjie Liao",
"Xinchen Yan",
"Yuwen Xiong",
"Wenyuan Zeng",
"Raquel Urtasun"
] | In this paper we address an important problem in self-driving, forecasting multi-pedestrian motion and their shared scene occupancy map, which is critical for safe navigation. Our contributions are two-fold. First, we advocate for predicting both the individual motions as well as the scene occupancy map in order to effectively deal with missing detections caused by postprocessing, e.g. confidence ... |
GRIT: Fast, Interpretable, and Verifiable Goal Recognition with Learned Decision Trees for Autonomous Driving | https://ieeexplore.ieee.org/document/9636279/ | [
"Cillian Brewitt",
"Balint Gyevnar",
"Samuel Garcin",
"Stefano V. Albrecht",
"Cillian Brewitt",
"Balint Gyevnar",
"Samuel Garcin",
"Stefano V. Albrecht"
] | It is important for autonomous vehicles to have the ability to infer the goals of other vehicles (goal recognition), in order to safely interact with other vehicles and predict their future trajectories. This is a difficult problem, especially in urban environments with interactions between many vehicles. Goal recognition methods must be fast to run in real time and make accurate inferences. As au... |
CovarianceNet: Conditional Generative Model for Correct Covariance Prediction in Human Motion Prediction | https://ieeexplore.ieee.org/document/9635968/ | [
"Aleksey Postnikov",
"Aleksander Gamayunov",
"Gonzalo Ferrer",
"Aleksey Postnikov",
"Aleksander Gamayunov",
"Gonzalo Ferrer"
] | The correct characterization of uncertainty when predicting human motion is equally important as the accuracy of this prediction. We present a new method to correctly predict the uncertainty associated with the predicted distribution of future trajectories. Our approach, CovariaceNet, is based on a Conditional Generative Model with Gaussian latent variables in order to predict the parameters of a ... |
State Estimation and Model-Predictive Control for Multi-Robot Handling and Tracking of AGV Motions using iGPS | https://ieeexplore.ieee.org/document/9636116/ | [
"Christoph Storm",
"Henrik Hose",
"Robert H. Schmitt",
"Christoph Storm",
"Henrik Hose",
"Robert H. Schmitt"
] | In this paper, we present a solution for simultaneous handling of large components with industrial robots performing synchronized motions with an AGV in flexible flow assembly. For this purpose, we implement an Extended Kalman Filter with a global localization system to track an AGV and multiple manipulators. We propose a model-predictive controller for force compliance and trajectory tracking in ... |
Benchmarking Off-The-Shelf Solutions to Robotic Assembly Tasks | https://ieeexplore.ieee.org/document/9636586/ | [
"Wenzhao Lian",
"Tim Kelch",
"Dirk Holz",
"Adam Norton",
"Stefan Schaal",
"Wenzhao Lian",
"Tim Kelch",
"Dirk Holz",
"Adam Norton",
"Stefan Schaal"
] | In recent years, many learning based approaches have been studied to realize robotic manipulation and assembly tasks, often including vision and force/tactile feedback. How-ever, it is unclear what the baseline state-of-the-art performance is and what the bottleneck problems are. In this work, we evaluate off-the-shelf (OTS) industrial solutions on a recently introduced benchmark, the National Ins... |
Assembly Sequence Generation for New Objects via Experience Learned from Similar Object | https://ieeexplore.ieee.org/document/9636531/ | [
"Zhongxiang Zhou",
"Rong Xiong",
"Zexi Chen",
"Yue Wang",
"Zhongxiang Zhou",
"Rong Xiong",
"Zexi Chen",
"Yue Wang"
] | Assembly orders of components have direct influence on feasibility and efficiency of assembly process in manufacturing and are usually defined by experienced operators. To automate the assembly sequence generation process, we present a method using the idea of case-based reasoning, which can take advantage of experience of a reference assembly to generate the assembly sequence of a new assembly. F... |
Combining Learning from Demonstration with Learning by Exploration to Facilitate Contact-Rich Tasks | https://ieeexplore.ieee.org/document/9636417/ | [
"Yunlei Shi",
"Zhaopeng Chen",
"Yansong Wu",
"Dimitri Henkel",
"Sebastian Riedel",
"Hongxu Liu",
"Qian Feng",
"Jianwei Zhang",
"Yunlei Shi",
"Zhaopeng Chen",
"Yansong Wu",
"Dimitri Henkel",
"Sebastian Riedel",
"Hongxu Liu",
"Qian Feng",
"Jianwei Zhang"
] | Collaborative robots are expected to work alongside humans and directly replace human workers in some cases, thus effectively responding to rapid changes in assembly lines. Current methods for programming contact-rich tasks, particularly in heavily constrained spaces, tend to be fairly inefficient. Therefore, faster and more intuitive approaches are urgently required for robot teaching. This study... |
Learn to Differ: Sim2Real Small Defection Segmentation Network | https://ieeexplore.ieee.org/document/9636491/ | [
"Zexi Chen",
"Zheyuan Huang",
"Hongxiang Yu",
"Zhongxiang Zhou",
"Yunkai Wang",
"Xuecheng Xu",
"Qimeng Tan",
"Yue Wang",
"Rong Xiong",
"Zexi Chen",
"Zheyuan Huang",
"Hongxiang Yu",
"Zhongxiang Zhou",
"Yunkai Wang",
"Xuecheng Xu",
"Qimeng Tan",
"Yue Wang",
"Rong Xiong"
] | Recent studies on deep-learning-based small defection segmentation approaches are trained in specific settings and tend to be limited by fixed context. Throughout the training, the network inevitably learns the representation of the background of the training data before figuring out the defection. They underperform in the inference stage once the context changed and can only be solved by training... |
TUPPer-Map: Temporal and Unified Panoptic Perception for 3D Metric-Semantic Mapping | https://ieeexplore.ieee.org/document/9636599/ | [
"Zhiliu Yang",
"Chen Liu",
"Zhiliu Yang",
"Chen Liu"
] | In this paper, we propose TUPPer-Map, a metric-semantic mapping framework based on the unified panoptic segmentation and temporal data association. In contrast to the previous mapping method, our framework integrates the data association stage into the holistic pixel-level segmentation stage in an end-to-end fashion, taking advantage of both intra-frame and inter-frame spatial and temporal knowled... |
Local Memory Attention for Fast Video Semantic Segmentation | https://ieeexplore.ieee.org/document/9636192/ | [
"Matthieu Paul",
"Martin Danelljan",
"Luc Van Gool",
"Radu Timofte",
"Matthieu Paul",
"Martin Danelljan",
"Luc Van Gool",
"Radu Timofte"
] | We propose a novel neural network module that transforms an existing single-frame semantic segmentation model into a video semantic segmentation pipeline. In contrast to prior works, we strive towards a simple, fast, and general module that can be integrated into virtually any single-frame architecture. Our approach aggregates a rich representation of the semantic information in past frames into a... |
LiDAR-based Drivable Region Detection for Autonomous Driving | https://ieeexplore.ieee.org/document/9636289/ | [
"Hanzhang Xue",
"Hao Fu",
"Ruike Ren",
"Jintao Zhang",
"Bokai Liu",
"Yiming Fan",
"Bin Dai",
"Hanzhang Xue",
"Hao Fu",
"Ruike Ren",
"Jintao Zhang",
"Bokai Liu",
"Yiming Fan",
"Bin Dai"
] | For autonomous driving, drivable region detection is one of the most basic and essential tasks. In this paper, a novel LiDAR-based drivable region detection algorithm which could output a complete, accurate and stable result is proposed. To promote the completeness of the detection result, the Bayesian generalized kernel inference and bilateral filtering are utilized to estimate the attribute of t... |
CP-loss: Connectivity-preserving Loss for Road Curb Detection in Autonomous Driving with Aerial Images | https://ieeexplore.ieee.org/document/9636060/ | [
"Zhenhua Xu",
"Yuxiang Sun",
"Lujia Wang",
"Ming Liu",
"Zhenhua Xu",
"Yuxiang Sun",
"Lujia Wang",
"Ming Liu"
] | Road curb detection is important for autonomous driving. It can be used to determine road boundaries to constrain vehicles on roads, so that potential accidents could be avoided. Most of the current methods detect road curbs online using vehicle-mounted sensors, such as cameras or 3-D Lidars. However, these methods usually suffer from severe occlusion issues. Especially in highly-dynamic traffic e... |
Semantic Image Alignment for Vehicle Localization | https://ieeexplore.ieee.org/document/9636517/ | [
"Markus Herb",
"Matthias Lemberger",
"Marcel M. Schmitt",
"Alexander Kurz",
"Tobias Weiherer",
"Nassir Navab",
"Federico Tombari",
"Markus Herb",
"Matthias Lemberger",
"Marcel M. Schmitt",
"Alexander Kurz",
"Tobias Weiherer",
"Nassir Navab",
"Federico Tombari"
] | Accurate and reliable localization is a fundamental requirement for autonomous vehicles to use map information in higher-level tasks such as navigation or planning. In this paper, we present a novel approach to vehicle localization in dense semantic maps, including vectorized high-definition maps or 3D meshes, using semantic segmentation from a monocular camera. We formulate the localization task ... |
ISSAFE: Improving Semantic Segmentation in Accidents by Fusing Event-based Data | https://ieeexplore.ieee.org/document/9636109/ | [
"Jiaming Zhang",
"Kailun Yang",
"Rainer Stiefelhagen",
"Jiaming Zhang",
"Kailun Yang",
"Rainer Stiefelhagen"
] | Ensuring the safety of all traffic participants is a prerequisite for bringing intelligent vehicles closer to practical applications. The assistance system should not only achieve high accuracy under normal conditions, but obtain robust perception against extreme situations. However, traffic accidents that involve object collisions, deformations, overturns, etc., yet unseen in most training sets, ... |
SNE-RoadSeg+: Rethinking Depth-Normal Translation and Deep Supervision for Freespace Detection | https://ieeexplore.ieee.org/document/9636723/ | [
"Hengli Wang",
"Rui Fan",
"Peide Cai",
"Ming Liu",
"Hengli Wang",
"Rui Fan",
"Peide Cai",
"Ming Liu"
] | Freespace detection is a fundamental component of autonomous driving perception. Recently, deep convolutional neural networks (DCNNs) have achieved impressive performance for this task. In particular, SNE-RoadSeg, our previously proposed method based on a surface normal estimator (SNE) and a data-fusion DCNN (RoadSeg), has achieved impressive performance in freespace detection. However, SNE-RoadSe... |
Coarse-to-fine Semantic Localization with HD Map for Autonomous Driving in Structural Scenes | https://ieeexplore.ieee.org/document/9635923/ | [
"Chengcheng Guo",
"Minjie Lin",
"Heyang Guo",
"Pengpeng Liang",
"Erkang Cheng",
"Chengcheng Guo",
"Minjie Lin",
"Heyang Guo",
"Pengpeng Liang",
"Erkang Cheng"
] | Robust and accurate localization is an essential component for robotic navigation and autonomous driving. The use of cameras for localization with high definition map (HD Map) provides an affordable localization sensor set. Existing methods suffer from pose estimation failure due to error prone data association or initialization with accurate initial pose requirement. In this paper, we propose a c... |
High Accuracy Three-Dimensional Self-Localization using Visual Markers and Inertia Measurement Unit | https://ieeexplore.ieee.org/document/9636749/ | [
"Kunihiro Ogata",
"Hideyuki Tanaka",
"Yoshio Matsumoto",
"Kunihiro Ogata",
"Hideyuki Tanaka",
"Yoshio Matsumoto"
] | Technologies for estimating self-position and orientation are important for both humans and robots. These technologies allow robots to perform tasks such as carrying objects and allow people to reach their destinations. Although self-position estimation technologies using GPS and laser rangefinders have been developed, few methods can be used by both humans and robots. Therefore, we developed a me... |
Online Spatio-temporal Calibration of Tightly-coupled Ultrawideband-aided Inertial Localization | https://ieeexplore.ieee.org/document/9636625/ | [
"Abhishek Goudar",
"Angela P. Schoellig",
"Abhishek Goudar",
"Angela P. Schoellig"
] | The combination of ultrawideband (UWB) radios and inertial measurement units (IMU) can provide accurate positioning in environments where the Global Positioning System (GPS) service is either unavailable or has unsatisfactory performance. The two sensors, IMU and UWB radio, are often not co-located on a moving system. The UWB radio is typically located at the extremities of the system to ensure re... |
SemSegMap – 3D Segment-based Semantic Localization | https://ieeexplore.ieee.org/document/9636156/ | [
"Andrei Cramariuc",
"Florian Tschopp",
"Nikhilesh Alatur",
"Stefan Benz",
"Tillmann Falck",
"Marius Brühlmeier",
"Benjamin Hahn",
"Juan Nieto",
"Roland Siegwart",
"Andrei Cramariuc",
"Florian Tschopp",
"Nikhilesh Alatur",
"Stefan Benz",
"Tillmann Falck",
"Marius Brühlmeier",
"Benjamin Hahn",
"Juan Nieto",
"Roland Siegwart"
] | Localization is an essential task for mobile autonomous robotic systems that want to use pre-existing maps or create new ones in the context of SLAM. Today, many robotic platforms are equipped with high-accuracy 3D LiDAR sensors, which allow a geometric mapping, and cameras able to provide semantic cues of the environment. Segment-based mapping and localization have been applied with great success... |
Recalling Direct 2D-3D Matches for Large-Scale Visual Localization | https://ieeexplore.ieee.org/document/9635897/ | [
"Zhuo Song",
"Chuting Wang",
"Yuqian Liu",
"Shuhan Shen",
"Zhuo Song",
"Chuting Wang",
"Yuqian Liu",
"Shuhan Shen"
] | Estimating the 6-DoF camera pose of an image with respect to a 3D scene model, known as visual localization, is a fundamental problem in many computer vision and robotics tasks. Among various visual localization methods, the direct 2D-3D matching method has become the preferred method for many practical applications due to its computational efficiency. When using direct 2D-3D matching methods in l... |
On Fault Classification in Connected Autonomous Vehicles Using Supervised Machine Learning | https://ieeexplore.ieee.org/document/9636741/ | [
"Abdelrahman Khalil",
"Mohammad Al Janaideh",
"Abdelrahman Khalil",
"Mohammad Al Janaideh"
] | Different health-monitoring techniques were considered in the literature to enhance the safety and stability of Connected Autonomous Vehicle (CAV) platoons. The health-monitoring processes include fault detection, localization, and mitigation. It is evident that mitigating these faults is faster and more reliable if the fault structure is known. To this end, we consider classifying the fault class... |
Autonomous Drone Racing with Deep Reinforcement Learning | https://ieeexplore.ieee.org/document/9636053/ | [
"Yunlong Song",
"Mats Steinweg",
"Elia Kaufmann",
"Davide Scaramuzza",
"Yunlong Song",
"Mats Steinweg",
"Elia Kaufmann",
"Davide Scaramuzza"
] | In many robotic tasks, such as autonomous drone racing, the goal is to travel through a set of waypoints as fast as possible. A key challenge for this task is planning the timeoptimal trajectory, which is typically solved by assuming perfect knowledge of the waypoints to pass in advance. The resulting solution is either highly specialized for a single-track layout, or suboptimal due to simplifying... |
Connecting Deep-Reinforcement-Learning-based Obstacle Avoidance with Conventional Global Planners using Waypoint Generators | https://ieeexplore.ieee.org/document/9636039/ | [
"Linh Kästner",
"Xinlin Zhao",
"Teham Buiyan",
"Junhui Li",
"Zhengcheng Shen",
"Jens Lambrecht",
"Cornelius Marx",
"Linh Kästner",
"Xinlin Zhao",
"Teham Buiyan",
"Junhui Li",
"Zhengcheng Shen",
"Jens Lambrecht",
"Cornelius Marx"
] | Deep Reinforcement Learning has emerged as an efficient dynamic obstacle avoidance method in highly dynamic environments. It has the potential to replace overly conservative or inefficient navigation approaches. However, integrating Deep Reinforcement Learning into existing navigation systems is still an open frontier due to the myopic nature of Deep-Reinforcement-Learning-based navigation, which ... |
Unsupervised Traffic Scene Generation with Synthetic 3D Scene Graphs | https://ieeexplore.ieee.org/document/9636318/ | [
"Artem Savkin",
"Rachid Ellouze",
"Nassir Navab",
"Federico Tombari",
"Artem Savkin",
"Rachid Ellouze",
"Nassir Navab",
"Federico Tombari"
] | Image synthesis driven by computer graphics achieved recently a remarkable realism, yet synthetic image data generated this way reveals a significant domain gap with respect to real-world data. This is especially true in autonomous driving scenarios, which represent a critical aspect for over-coming utilizing synthetic data for training neural networks. We propose a method based on domain-invarian... |
Minimizing Safety Interference for Safe and Comfortable Automated Driving with Distributional Reinforcement Learning | https://ieeexplore.ieee.org/document/9636847/ | [
"Danial Kamran",
"Tizian Engelgeh",
"Marvin Busch",
"Johannes Fischer",
"Christoph Stiller",
"Danial Kamran",
"Tizian Engelgeh",
"Marvin Busch",
"Johannes Fischer",
"Christoph Stiller"
] | Despite recent advances in reinforcement learning (RL), its application in safety critical domains like autonomous vehicles is still challenging. Although penalizing RL agents for risky situations can help to learn safe policies, it may also lead to highly conservative behavior. In this paper, we propose a distributional RL framework in order to learn adaptive policies which allow to tune their le... |
Autonomous Vehicle Navigation in Semi-structured Environments Based on Sparse Waypoints and LiDAR Road-tracking | https://ieeexplore.ieee.org/document/9636082/ | [
"Kosmas Tsiakas",
"Ioannis Kostavelis",
"Antonios Gasteratos",
"Dimitrios Tzovaras",
"Kosmas Tsiakas",
"Ioannis Kostavelis",
"Antonios Gasteratos",
"Dimitrios Tzovaras"
] | During the last decades, the research endeavours on autonomous driving found great resonance in Advanced Driver-Assistance Solutions that equipped the contemporary civilian vehicles and significantly boosted their driver-less mobility. The existing applications are mostly focused on urban scenarios where signs, road lanes and markers are well defined and ordered favouring the motion of the vehicle... |
Delay Aware Universal Notice Network: Real world multi-robot transfer learning | https://ieeexplore.ieee.org/document/9635917/ | [
"Samuel Beaussant",
"Sébastien Lengagne",
"Benoit Thuilot",
"Olivier Stasse",
"Samuel Beaussant",
"Sébastien Lengagne",
"Benoit Thuilot",
"Olivier Stasse"
] | General purpose simulators provide cheap training data to learn complex robotic skills. However, the transition from simulation to reality is often very challenging for the agent. One major issue is the delay on the physical robot that may deteriorate the performance of the deployed agent. Furthermore, once a successfully trained learning-based control policy is available, re-purposing the knowled... |
Domain Curiosity: Learning Efficient Data Collection Strategies for Domain Adaptation | https://ieeexplore.ieee.org/document/9635864/ | [
"Karol Arndt",
"Oliver Struckmeier",
"Ville Kyrki",
"Karol Arndt",
"Oliver Struckmeier",
"Ville Kyrki"
] | Domain adaptation is a common problem in robotics, with applications such as transferring policies from simulation to real world and lifelong learning. Performing such adaptation, however, requires informative data about the environment to be available during the adaptation. In this paper, we present domain curiosity—a method of training exploratory policies that are explicitly optimized to provid... |
Knowledge Transfer across Imaging Modalities Via Simultaneous Learning of Adaptive Autoencoders for High-Fidelity Mobile Robot Vision | https://ieeexplore.ieee.org/document/9636360/ | [
"Md Mahmudur Rahman",
"Tauhidur Rahman",
"Donghyun Kim",
"Mohammad Arif Ul Alam",
"Md Mahmudur Rahman",
"Tauhidur Rahman",
"Donghyun Kim",
"Mohammad Arif Ul Alam"
] | Enabling mobile robots for solving challenging and diverse shape, texture, and motion related tasks with high fidelity vision requires the integration of novel multimodal imaging sensors and advanced fusion techniques. However, it is associated with high cost, power, hardware modification, and computing requirements which limit its scalability. In this paper, we propose a novel Simultaneously Lear... |
Bayesian Meta-Learning for Few-Shot Policy Adaptation Across Robotic Platforms | https://ieeexplore.ieee.org/document/9636628/ | [
"Ali Ghadirzadeh",
"Xi Chen",
"Petra Poklukar",
"Chelsea Finn",
"Mårten Björkman",
"Danica Kragic",
"Ali Ghadirzadeh",
"Xi Chen",
"Petra Poklukar",
"Chelsea Finn",
"Mårten Björkman",
"Danica Kragic"
] | Reinforcement learning methods can achieve significant performance but require a large amount of training data collected on the same robotic platform. A policy trained with expensive data is rendered useless after making even a minor change to the robot hardware. In this paper, we address the challenging problem of adapting a policy, trained to perform a task, to a novel robotic hardware platform ... |
Shaping Progressive Net of Reinforcement Learning for Policy Transfer with Human Evaluative Feedback | https://ieeexplore.ieee.org/document/9636061/ | [
"Rongshun Juan",
"Jie Huang",
"Randy Gomez",
"Keisuke Nakamura",
"Qixin Sha",
"Bo He",
"Guangliang Li",
"Rongshun Juan",
"Jie Huang",
"Randy Gomez",
"Keisuke Nakamura",
"Qixin Sha",
"Bo He",
"Guangliang Li"
] | Deep reinforcement learning has achieved significant success in many fields, but will confront sampling efficiency and safety problems when applying to robot control in the real world. Sim-to-real transfer learning was proposed to make use of samples in the simulation and overcome the gap between simulation and real world. In this paper, we focus on improving Progressive Neural Network — an effect... |
A Conformal Mapping-based Framework for Robot-to-Robot and Sim-to-Real Transfer Learning | https://ieeexplore.ieee.org/document/9636682/ | [
"Shijie Gao",
"Nicola Bezzo",
"Shijie Gao",
"Nicola Bezzo"
] | This paper presents a novel method for transferring motion planning and control policies between a teacher and a learner robot. With this work, we propose to reduce the sim-to-real gap, transfer knowledge designed for a specific system into a different robot, and compensate for system aging and failures. To solve this problem we introduce a Schwarz–Christoffel mapping-based method to geometrically... |
On Explainability and Sensor-Adaptability of a Robot Tactile Texture Representation Using a Two-Stage Recurrent Networks | https://ieeexplore.ieee.org/document/9636380/ | [
"Ruihan Gao",
"Tian Tian",
"Zhiping Lin",
"Yan Wu",
"Ruihan Gao",
"Tian Tian",
"Zhiping Lin",
"Yan Wu"
] | The ability to simultaneously distinguish objects, materials, and their associated physical properties is one fundamental function of the sense of touch. Recent advances in the development of tactile sensors and machine learning techniques allow more accurate and complex modelling of robotic tactile sensations. However, many state-of-the-art (SotA) approaches focus solely on constructing black-box... |
EVReflex: Dense Time-to-Impact Prediction for Event-based Obstacle Avoidance | https://ieeexplore.ieee.org/document/9636327/ | [
"Celyn Walters",
"Simon Hadfield",
"Celyn Walters",
"Simon Hadfield"
] | The broad scope of obstacle avoidance has led to many kinds of computer vision-based approaches. Despite its popularity, it is not a solved problem. Traditional computer vision techniques using cameras and depth sensors often focus on static scenes, or rely on priors about the obstacles. Recent developments in bio-inspired sensors present event cameras as a compelling choice for dynamic scenes. Al... |
PTT: Point-Track-Transformer Module for 3D Single Object Tracking in Point Clouds | https://ieeexplore.ieee.org/document/9636821/ | [
"Jiayao Shan",
"Sifan Zhou",
"Zheng Fang",
"Yubo Cui",
"Jiayao Shan",
"Sifan Zhou",
"Zheng Fang",
"Yubo Cui"
] | 3D single object tracking is a key issue for robotics. In this paper, we propose a transformer module called Point-Track-Transformer (PTT) for point cloud-based 3D single object tracking. PTT module contains three blocks for feature embedding, position encoding, and self-attention feature computation. Feature embedding aims to place features closer in the embedding space if they have similar seman... |
A Registration-aided Domain Adaptation Network for 3D Point Cloud Based Place Recognition | https://ieeexplore.ieee.org/document/9635878/ | [
"Zhijian Qiao",
"Hanjiang Hu",
"Weiang Shi",
"Siyuan Chen",
"Zhe Liu",
"Hesheng Wang",
"Zhijian Qiao",
"Hanjiang Hu",
"Weiang Shi",
"Siyuan Chen",
"Zhe Liu",
"Hesheng Wang"
] | In the field of large-scale SLAM for autonomous driving and mobile robotics, 3D point cloud based place recognition has aroused significant research interest due to its robustness to changing environments with drastic daytime and weather variance. However, it is time-consuming and effort-costly to obtain high-quality point cloud data for place recognition model training and ground truth for regist... |
iNeRF: Inverting Neural Radiance Fields for Pose Estimation | https://ieeexplore.ieee.org/document/9636708/ | [
"Lin Yen-Chen",
"Pete Florence",
"Jonathan T. Barron",
"Alberto Rodriguez",
"Phillip Isola",
"Tsung-Yi Lin",
"Lin Yen-Chen",
"Pete Florence",
"Jonathan T. Barron",
"Alberto Rodriguez",
"Phillip Isola",
"Tsung-Yi Lin"
] | We present iNeRF, a framework that performs mesh-free pose estimation by "inverting" a Neural Radiance Field (NeRF). NeRFs have been shown to be remarkably effective for the task of view synthesis — synthesizing photorealistic novel views of real-world scenes or objects. In this work, we investigate whether we can apply analysis-by-synthesis via NeRF for mesh-free, RGB-only 6DoF pose estimation – ... |
RaP-Net: A Region-wise and Point-wise Weighting Network to Extract Robust Features for Indoor Localization | https://ieeexplore.ieee.org/document/9636248/ | [
"Dongjiang Li",
"Jinyu Miao",
"Xuesong Shi",
"Yuxin Tian",
"Qiwei Long",
"Tianyu Cai",
"Ping Guo",
"Hongfei Yu",
"Wei Yang",
"Haosong Yue",
"Qi Wei",
"Fei Qiao",
"Dongjiang Li",
"Jinyu Miao",
"Xuesong Shi",
"Yuxin Tian",
"Qiwei Long",
"Tianyu Cai",
"Ping Guo",
"Hongfei Yu",
"Wei Yang",
"Haosong Yue",
"Qi Wei",
"Fei Qiao"
] | Feature extraction plays an important role in visual localization. Unreliable features on dynamic objects or repetitive regions will interfere with feature matching and challenge indoor localization greatly. To address the problem, we propose a novel network, RaP-Net, to simultaneously predict region-wise invariability and point-wise reliability, and then extract features by considering both of th... |
Differentiable Factor Graph Optimization for Learning Smoothers | https://ieeexplore.ieee.org/document/9636300/ | [
"Brent Yi",
"Michelle A. Lee",
"Alina Kloss",
"Roberto Martín-Martín",
"Jeannette Bohg",
"Brent Yi",
"Michelle A. Lee",
"Alina Kloss",
"Roberto Martín-Martín",
"Jeannette Bohg"
] | A recent line of work has shown that end-to-end optimization of Bayesian filters can be used to learn state estimators for systems whose underlying models are difficult to hand-design or tune, while retaining the core advantages of probabilistic state estimation. As an alternative approach for state estimation in these settings, we present an end-to-end approach for learning state estimators model... |
Attention Augmented ConvLSTM for Environment Prediction | https://ieeexplore.ieee.org/document/9636386/ | [
"Bernard Lange",
"Masha Itkina",
"Mykel J. Kochenderfer",
"Bernard Lange",
"Masha Itkina",
"Mykel J. Kochenderfer"
] | Safe and proactive planning in robotic systems generally requires accurate predictions of the environment. Prior work on environment prediction applied video frame prediction techniques to bird’s-eye view environment representations, such as occupancy grids. ConvLSTM-based frameworks used previously often result in significant blurring of the predictions, loss of static environment structure, and ... |
Control-Aware Design Optimization for Bio-Inspired Quadruped Robots | https://ieeexplore.ieee.org/document/9636415/ | [
"Flavio De Vincenti",
"Dongho Kang",
"Stelian Coros",
"Flavio De Vincenti",
"Dongho Kang",
"Stelian Coros"
] | We present a control-aware design optimization method for quadrupedal robots. In particular, we show that it is possible to analytically differentiate typical, inverse dynamics-based whole body controllers with respect to design parameters, and that gradient-based methods can be used to efficiently improve an initial morphological design according to well-established metrics. We apply our design o... |
Embedding a Nonlinear Strict Oscillatory Mode into a Segmented Leg | https://ieeexplore.ieee.org/document/9636605/ | [
"Anna Sesselmann",
"Florian Loeffl",
"Cosimo Della Santina",
"Maximo A. Roa",
"Alin Albu-Schäffer",
"Anna Sesselmann",
"Florian Loeffl",
"Cosimo Della Santina",
"Maximo A. Roa",
"Alin Albu-Schäffer"
] | Robotic legs often lag behind the performance of their biological counterparts. The inherent passive dynamics of natural legs largely influences the locomotion and can be abstracted through the spring-loaded inverted pendulum (SLIP) model. This model is often approximated in physical robotic legs using a leg with minimal mass. Our work aims to embed the SLIP dynamics by using a nonlinear strict os... |
A Novel Design of Mobile Robotic System for Opening and Transitioning Through a Watertight Ship Door | https://ieeexplore.ieee.org/document/9635942/ | [
"Wenyu Zuo",
"Rahul Venkatraman",
"Gangbing Song",
"Zheng Chen",
"Wenyu Zuo",
"Rahul Venkatraman",
"Gangbing Song",
"Zheng Chen"
] | Recent offshore drilling activities have dramatically bloomed oil and gas production. Due to extreme weather, such as hurricanes and tsunamis, offshore oil platforms may need to be constantly monitored in case of unexpected dangers. Using robots to monitor and prevent these dangerous situations is a cost-effective and safer solution compared to any human involvement. However, one major drawback fo... |
Designing Rotary Linkages for Polar Motions | https://ieeexplore.ieee.org/document/9636587/ | [
"Aravind Baskar",
"Chang Liu",
"Mark Plecnik",
"Jonathan D. Hauenstein",
"Aravind Baskar",
"Chang Liu",
"Mark Plecnik",
"Jonathan D. Hauenstein"
] | Polar linkages have two degrees-of-freedom (DOF) where one input joint angle controls the length of a radial segment while another controls its angle. Considering a theoretical planar robot model, this mapping between joint angles to output motions can be shown to be energetically advantageous over the ubiquitous two-revolute linkage. Since a polar linkage’s typical construction involves a moving ... |
Trajectory Optimization For Rendezvous Planning Using Quadratic Bézier Curves | https://ieeexplore.ieee.org/document/9636535/ | [
"Satyanarayana G. Manyam",
"David W. Casbeer",
"Isaac E. Weintraub",
"Colin Taylor",
"Satyanarayana G. Manyam",
"David W. Casbeer",
"Isaac E. Weintraub",
"Colin Taylor"
] | In this paper, we consider a trajectory planning problem where an autonomous vehicle aims to rendezvous with another cooperating vehicle in minimum time. The first vehicle has kinematic constraints, consequently feasible trajectories must have a maximum curvature less than a specified limit. Rendezvous is said to occur at the instant that the two vehicles are collocated with the same heading. We p... |
Unsupervised Path Regression Networks | https://ieeexplore.ieee.org/document/9636818/ | [
"Michal Pándy",
"Daniel Lenton",
"Ronald Clark",
"Michal Pándy",
"Daniel Lenton",
"Ronald Clark"
] | We demonstrate that challenging shortest path problems can be solved via direct spline regression from a neural network, trained in an unsupervised manner (i.e. without requiring ground truth optimal paths for training). To achieve this, we derive a geometry-dependent optimal cost function whose minima guarantees collision-free solutions. Our method beats state-of-the-art supervised learning basel... |
Path-constrained optimal trajectory planning for robot manipulators with obstacle avoidance | https://ieeexplore.ieee.org/document/9636674/ | [
"Yalun Wen",
"Prabhakar R. Pagilla",
"Yalun Wen",
"Prabhakar R. Pagilla"
] | In this paper, we develop a novel path-constrained and collision-free optimal trajectory planning algorithm for robot manipulators in the presence of obstacles for the following problem: Given a desired sequence of discrete waypoints of robot configurations, a set of robot kinematic and dynamic constraints, and a set of obstacles, determine a time and jerk optimal and collision-free trajectory for... |
CR-LSTM: Collision-prior Guided Social Refinement for Pedestrian Trajectory Prediction | https://ieeexplore.ieee.org/document/9636722/ | [
"Zhaoxin Su",
"Sanyuan Zhang",
"Wei Hua",
"Zhaoxin Su",
"Sanyuan Zhang",
"Wei Hua"
] | Pedestrian trajectory prediction is a challenge because of the complex social interactions in context and the elusive intention of each pedestrian. Collision avoidance is one of the most common social interactions in real world, while existing data-driven works have not handled it well yet. In order to address this issue, we propose a framework that considers the theory about the minimum distance ... |
Robust and Recursively Feasible Real-Time Trajectory Planning in Unknown Environments | https://ieeexplore.ieee.org/document/9636048/ | [
"Inkyu Jang",
"Dongjae Lee",
"Seungjae Lee",
"H. Jin Kim",
"Inkyu Jang",
"Dongjae Lee",
"Seungjae Lee",
"H. Jin Kim"
] | Motion planners for mobile robots in unknown environments face the challenge of simultaneously maintaining both robustness against unmodeled uncertainties and persistent feasibility of the trajectory-finding problem. That is, while dealing with uncertainties, a motion planner must update its trajectory, adapting to the newly revealed environment in real-time; failing to do so may involve unsafe ci... |
PILOT: Efficient Planning by Imitation Learning and Optimisation for Safe Autonomous Driving | https://ieeexplore.ieee.org/document/9636862/ | [
"Henry Pulver",
"Francisco Eiras",
"Ludovico Carozza",
"Majd Hawasly",
"Stefano V. Albrecht",
"Subramanian Ramamoorthy",
"Henry Pulver",
"Francisco Eiras",
"Ludovico Carozza",
"Majd Hawasly",
"Stefano V. Albrecht",
"Subramanian Ramamoorthy"
] | Achieving a proper balance between planning quality, safety and efficiency is a major challenge for autonomous driving. Optimisation-based motion planners are capable of producing safe, smooth and comfortable plans, but often at the cost of runtime efficiency. On the other hand, naïvely deploying trajectories produced by efficient-to-run deep imitation learning approaches might risk compromising s... |
Exploring Imitation Learning for Autonomous Driving with Feedback Synthesizer and Differentiable Rasterization | https://ieeexplore.ieee.org/document/9636795/ | [
"Jinyun Zhou",
"Rui Wang",
"Xu Liu",
"Yifei Jiang",
"Shu Jiang",
"Jiaming Tao",
"Jinghao Miao",
"Shiyu Song",
"Jinyun Zhou",
"Rui Wang",
"Xu Liu",
"Yifei Jiang",
"Shu Jiang",
"Jiaming Tao",
"Jinghao Miao",
"Shiyu Song"
] | We present a learning-based planner that aims to robustly drive a vehicle by mimicking human drivers’ driving behavior. We leverage a mid-to-mid approach that allows us to manipulate the input to our imitation learning network freely. With that in mind, we propose a novel feedback synthesizer for data augmentation. It allows our agent to gain more driving experience in various previously unseen en... |
Distributed Event- and Self-Triggered Coverage Control with Speed Constrained Unicycle Robots | https://ieeexplore.ieee.org/document/9636524/ | [
"Yuni Zhou",
"Lingxuan Kong",
"Stefan Sosnowski",
"Qingchen Liu",
"Sandra Hirche",
"Yuni Zhou",
"Lingxuan Kong",
"Stefan Sosnowski",
"Qingchen Liu",
"Sandra Hirche"
] | Voronoi coverage control is a particular problem of importance in the area of multi-robot systems, which considers a network of multiple autonomous robots, tasked with optimally covering a large area. This is a common task for fleets of fixed-wing Unmanned Aerial Vehicles (UAVs), which are described in this work by a unicycle model with constant forward-speed constraints. We develop event-based co... |
Combined Routing and Scheduling of Heterogeneous Transport and Service Agents | https://ieeexplore.ieee.org/document/9636684/ | [
"Saaketh Narayan",
"James Paulos",
"Steven W. Chen",
"Sandeep Manjanna",
"Vijay Kumar",
"Saaketh Narayan",
"James Paulos",
"Steven W. Chen",
"Sandeep Manjanna",
"Vijay Kumar"
] | This paper investigates servicing waypoints in a wide area using collaborative deployments of vehicles with heterogeneous range and mobility constraints. We formulate a joint planning problem for a single transport truck and multiple service drones in which the truck is constrained to a road and must deploy a team of range-constrained drones to visit waypoints. The need to deploy, collect, and red... |
Encirclement Guaranteed Cooperative Pursuit with Robust Model Predictive Control | https://ieeexplore.ieee.org/document/9636127/ | [
"Chen Wang",
"Hua Chen",
"Jia Pan",
"Wei Zhang",
"Chen Wang",
"Hua Chen",
"Jia Pan",
"Wei Zhang"
] | This paper studies a novel encirclement guaranteed cooperative pursuit problem involving N pursuers and a single evader in an unbounded two-dimensional game domain. Throughout the game, the pursuers are required to maintain encirclement of the evader, i.e., the evader should always stay inside the convex hull generated by all the pursuers, in addition to achieving the classical capture condition. ... |
Path Optimization for Cooperative Mapping Using Multiple Robots with Limited Sensing Capabilities | https://ieeexplore.ieee.org/document/9635934/ | [
"Kyungseo Kim",
"Jinwhan Kim",
"Kyungseo Kim",
"Jinwhan Kim"
] | This study addresses the problem of path optimization for conducting a mapping mission using a multi-robot system with limited sensing capability, which aims to ensure efficient mapping with emphasis on the cooperative aspect of the mission. To achieve the cooperative mapping, a new path planning algorithm is proposed which can take advantage of the multi-robot system while dealing with the lack o... |
An Interleaved Approach to Trait-Based Task Allocation and Scheduling | https://ieeexplore.ieee.org/document/9636569/ | [
"Glen Neville",
"Andrew Messing",
"Harish Ravichandar",
"Seth Hutchinson",
"Sonia Chernova",
"Glen Neville",
"Andrew Messing",
"Harish Ravichandar",
"Seth Hutchinson",
"Sonia Chernova"
] | To realize effective heterogeneous multi-robot teams, researchers must leverage individual robots’ relative strengths and coordinate their individual behaviors. Specifically, heterogeneous multi-robot systems must answer three important questions: who (task allocation), when (scheduling), and how (motion planning). While specific variants of each of these problems are known to be NP-Hard, their in... |
Multi-robot Task Assignment for Aerial Tracking with Viewpoint Constraints | https://ieeexplore.ieee.org/document/9636719/ | [
"Aaron Ray",
"Alyssa Pierson",
"Hai Zhu",
"Javier Alonso-Mora",
"Daniela Rus",
"Aaron Ray",
"Alyssa Pierson",
"Hai Zhu",
"Javier Alonso-Mora",
"Daniela Rus"
] | We address the problem of assigning a team of drones to autonomously capture a set desired shots of a dynamic target in the presence of obstacles. We present a two-stage planning pipeline that generates offline an assignment of drone to shots and locally optimizes online the viewpoint. Given desired shot parameters, the high-level planner uses a visibility heuristic to predict good times for captu... |
POMP++: Pomcp-based Active Visual Search in unknown indoor environments | https://ieeexplore.ieee.org/document/9635866/ | [
"Francesco Giuliari",
"Alberto Castellini",
"Riccardo Berra",
"Alessio Del Bue",
"Alessandro Farinelli",
"Marco Cristani",
"Francesco Setti",
"Yiming Wang",
"Francesco Giuliari",
"Alberto Castellini",
"Riccardo Berra",
"Alessio Del Bue",
"Alessandro Farinelli",
"Marco Cristani",
"Francesco Setti",
"Yiming Wang"
] | In this paper, we focus on the problem of learning online an optimal policy for Active Visual Search (AVS) of objects in unknown indoor environments. We propose POMP++, a planning strategy that introduces a novel formulation on top of the classic Partially Observable Monte Carlo Planning (POMCP) framework, to allow training-free online policy learning in unknown environments. We present a new beli... |
DT-Loc: Monocular Visual Localization on HD Vector Map Using Distance Transforms of 2D Semantic Detections | https://ieeexplore.ieee.org/document/9636419/ | [
"Chi Zhang",
"Hao Liu",
"Hao Li",
"Kun Guo",
"Kuiyuan Yang",
"Rui Cai",
"Zhiwei Li",
"Chi Zhang",
"Hao Liu",
"Hao Li",
"Kun Guo",
"Kuiyuan Yang",
"Rui Cai",
"Zhiwei Li"
] | Localizing a vehicle on a prebuilt HD vector map is a prerequisite for many autonomous driving applications. Existing visual localization approaches usually require a separate local feature layer to function. The separate localization layer suffers from the robustness issue inherited from the local features. Also, it could be difficult to create a feature layer that aligns perfectly with an existi... |
Probabilistic Visual Navigation with Bidirectional Image Prediction | https://ieeexplore.ieee.org/document/9636340/ | [
"Noriaki Hirose",
"Shun Taguchi",
"Fei Xia",
"Roberto Martín-Martín",
"Kosuke Tahara",
"Masanori Ishigaki",
"Silvio Savarese",
"Noriaki Hirose",
"Shun Taguchi",
"Fei Xia",
"Roberto Martín-Martín",
"Kosuke Tahara",
"Masanori Ishigaki",
"Silvio Savarese"
] | Humans can robustly follow a visual trajectory defined by a sequence of images (i.e. a video) regardless of substantial changes in the environment or the presence of obstacles. We aim at endowing similar visual navigation capabilities to mobile robots solely equipped with a RGB fisheye camera. We propose a novel probabilistic visual navigation system that learns to follow a sequence of images with... |
Mapless Humanoid Navigation Using Learned Latent Dynamics | https://ieeexplore.ieee.org/document/9636593/ | [
"André Brandenburger",
"Diego Rodriguez",
"Sven Behnke",
"André Brandenburger",
"Diego Rodriguez",
"Sven Behnke"
] | In this paper, we propose a novel Deep Reinforcement Learning approach to address the mapless navigation problem, in which the locomotion actions of a humanoid robot are taken online based on the knowledge encoded in learned models. Planning happens by generating open-loop trajectories in a learned latent space that captures the dynamics of the environment. Our planner considers visual (RGB images... |
Success Weighted by Completion Time: A Dynamics-Aware Evaluation Criteria for Embodied Navigation | https://ieeexplore.ieee.org/document/9636743/ | [
"Naoki Yokoyama",
"Sehoon Ha",
"Dhruv Batra",
"Naoki Yokoyama",
"Sehoon Ha",
"Dhruv Batra"
] | We present Success weighted by Completion Time (SCT), a new metric for evaluating navigation performance for mobile robots. Several related works on navigation have used Success weighted by Path Length (SPL) as the primary method of evaluating the path an agent makes to a goal location, but SPL is limited in its ability to properly evaluate agents with complex dynamics. In contrast, SCT explicitly... |
A Bio-Inspired Multi-Sensor System for Robust Orientation and Position Estimation | https://ieeexplore.ieee.org/document/9635932/ | [
"Jia Xie",
"Xiaofeng He",
"Jun Mao",
"Lilian Zhang",
"Guoliang Han",
"Wenzhou Zhou",
"Xiaoping Hu",
"Jia Xie",
"Xiaofeng He",
"Jun Mao",
"Lilian Zhang",
"Guoliang Han",
"Wenzhou Zhou",
"Xiaoping Hu"
] | The nature animals have evolved highly efficient and robust organs that support their complex daily navigation tasks. To mimic animal’s navigation capability, we present a novel bio-inspired navigation system that draws inspirations from nature animals in this paper. The system consists of a three-axis magnetometer, a monocular camera, a micro inertial measurement unit (MIMU) and a polarization ca... |
Through the Looking Glass: Diminishing Occlusions in Robot Vision Systems with Mirror Reflections | https://ieeexplore.ieee.org/document/9636366/ | [
"Kentaro Yoshioka",
"Hidenori Okuni",
"Tuan Thanh Ta",
"Akihide Sai",
"Kentaro Yoshioka",
"Hidenori Okuni",
"Tuan Thanh Ta",
"Akihide Sai"
] | The quality of robot vision greatly affects the performance of automation systems, where occlusions stand as one of the biggest challenges. If the target is occluded from the sensor, detecting and grasping such objects become very challenging. For example, when multiple robot arms cooperate in a single workplace, occlusions will be created under the robot arm itself and hide objects underneath. Wh... |
Similarity-Aware Fusion Network for 3D Semantic Segmentation | https://ieeexplore.ieee.org/document/9636494/ | [
"Linqing Zhao",
"Jiwen Lu",
"Jie Zhou",
"Linqing Zhao",
"Jiwen Lu",
"Jie Zhou"
] | In this paper, we propose a similarity-aware fusion network (SAFNet) to adaptively fuse 2D images and 3D point clouds for 3D semantic segmentation. Existing fusion-based methods achieve superior performances by integrating information from multiple modalities. However, they heavily rely on the projection-based correspondence between 2D pixels and 3D points and can only perform the information fusi... |
RoRD: Rotation-Robust Descriptors and Orthographic Views for Local Feature Matching | https://ieeexplore.ieee.org/document/9636619/ | [
"Udit Singh Parihar",
"Aniket Gujarathi",
"Kinal Mehta",
"Satyajit Tourani",
"Sourav Garg",
"Michael Milford",
"K. Madhava Krishna",
"Udit Singh Parihar",
"Aniket Gujarathi",
"Kinal Mehta",
"Satyajit Tourani",
"Sourav Garg",
"Michael Milford",
"K. Madhava Krishna"
] | The use of local detectors and descriptors in typical computer vision pipelines works well until variations in viewpoint and appearance change become extreme. Past research in this area has typically focused on one of two approaches to this challenge: the use of projections into spaces more suitable for feature matching under extreme viewpoint changes, and attempting to learn features that are inh... |
Phase-SLAM: Mobile Structured Light Illumination for Full Body 3D Scanning | https://ieeexplore.ieee.org/document/9636457/ | [
"Xi Zheng",
"Rui Ma",
"Rui Gao",
"Qi Hao",
"Xi Zheng",
"Rui Ma",
"Rui Gao",
"Qi Hao"
] | Full body scanning plays an important role in automated industrial manufacture and inspection. It requires the fusion of multi-view point cloud data and consumes large computational resources when the geometry of corresponding point clouds are unknown. Structured Light Illumination (SLI) is one of the most promising indoor 3D imaging techniques, but also has the same weakness for fusing the multi-... |
Learning Environment Constraints in Collaborative Robotics: A Decentralized Leader-Follower Approach | https://ieeexplore.ieee.org/document/9636444/ | [
"Monimoy Bujarbaruah",
"Yvonne R. Stürz",
"Conrad Holda",
"Karl H. Johansson",
"Francesco Borrelli",
"Monimoy Bujarbaruah",
"Yvonne R. Stürz",
"Conrad Holda",
"Karl H. Johansson",
"Francesco Borrelli"
] | In this paper, we propose a leader-follower hierarchical strategy for two robots collaboratively transporting an object in a partially known environment with obstacles. Both robots sense the local surrounding environment and react to obstacles in their proximity. We consider no explicit communication, so the local environment information and the control actions are not shared between the robots. A... |
Rapid Convex Optimization of Centroidal Dynamics using Block Coordinate Descent | https://ieeexplore.ieee.org/document/9635856/ | [
"Paarth Shah",
"Avadesh Meduri",
"Wolfgang Merkt",
"Majid Khadiv",
"Ioannis Havoutis",
"Ludovic Righetti",
"Paarth Shah",
"Avadesh Meduri",
"Wolfgang Merkt",
"Majid Khadiv",
"Ioannis Havoutis",
"Ludovic Righetti"
] | In this paper we explore the use of block coordinate descent (BCD) to optimize the centroidal momentum dynamics for dynamically consistent multi-contact behaviors. The centroidal dynamics have recently received a large amount of attention in order to create physically realizable motions for robots with hands and feet while being computationally more tractable than full rigid body dynamics models. ... |
Real-Time Hamilton-Jacobi Reachability Analysis of Autonomous System With An FPGA | https://ieeexplore.ieee.org/document/9636410/ | [
"Minh Bui",
"Michael Lu",
"Reza Hojabr",
"Mo Chen",
"Arrvindh Shriraman",
"Minh Bui",
"Michael Lu",
"Reza Hojabr",
"Mo Chen",
"Arrvindh Shriraman"
] | Hamilton-Jacobi (HJ) reachability analysis is a powerful technique used to verify the safety of autonomous systems. HJ reachability is ideal for analysing nonlinear systems with disturbances and flexible set representations. A drawback to this approach is that it suffers from the curse of dimensionality, which prevents real-time deployment on safety-critical systems. In this paper, we show that a ... |
Pairwise Preferences-Based Optimization of a Path-Based Velocity Planner in Robotic Sealing Tasks | https://ieeexplore.ieee.org/document/9636184/ | [
"Loris Roveda",
"Beatrice Maggioni",
"Elia Marescotti",
"Asad Ali Shahid",
"Andrea Maria Zanchettin",
"Alberto Bemporad",
"Dario Piga",
"Loris Roveda",
"Beatrice Maggioni",
"Elia Marescotti",
"Asad Ali Shahid",
"Andrea Maria Zanchettin",
"Alberto Bemporad",
"Dario Piga"
] | Production plants are being re-designed to implement human-centered solutions. Especially considering high added-value operations, robots are required to optimize their behavior to achieve a task quality at least comparable to the one obtained by the skilled operators. A manual programming and tuning of the manipulator is not an efficient solution, requiring to adopt towards automated strategies. ... |
Sim2Sim Evaluation of a Novel Data-Efficient Differentiable Physics Engine for Tensegrity Robots | https://ieeexplore.ieee.org/document/9636783/ | [
"Kun Wang",
"Mridul Aanjaneya",
"Kostas Bekris",
"Kun Wang",
"Mridul Aanjaneya",
"Kostas Bekris"
] | Learning policies in simulation is promising for reducing human effort when training robot controllers. This is especially true for soft robots that are more adaptive and safe but also more difficult to accurately model and control. The sim2real gap is the main barrier to successfully transfer policies from simulation to a real robot. System identification can be applied to reduce this gap but tra... |
Soft Manipulator Fault Detection and Identification Using ANC-based LSTM | https://ieeexplore.ieee.org/document/9636868/ | [
"Haoyuan Gu",
"Hanjiang Hu",
"Hesheng Wang",
"Weidong Chen",
"Haoyuan Gu",
"Hanjiang Hu",
"Hesheng Wang",
"Weidong Chen"
] | Timely fault detection and identification (FDI) of soft manipulators are critical in the design of surgical systems to improve reliability. However, due to the intrinsic compliance of soft manipulators, their end effectors vibrate during the dynamic control process, which introduces noise into the measured signals and makes FDI of soft manipulators challenging. This paper proposes a novel method t... |
Position Control and Variable-Height Trajectory Tracking of a Soft Pneumatic Legged Robot | https://ieeexplore.ieee.org/document/9635966/ | [
"Zhichao Liu",
"Konstantinos Karydis",
"Zhichao Liu",
"Konstantinos Karydis"
] | Soft pneumatic legged robots show promise in their ability to traverse a range of different types of terrain, including natural unstructured terrain met in applications like precision agriculture. They can adapt their body morphology to the intricacies of the terrain at hand, thus enabling robust and resilient locomotion. In this paper we capitalize upon recent developments on soft pneumatic legge... |
Task Driven Skill Learning in a Soft-Robotic Arm | https://ieeexplore.ieee.org/document/9636812/ | [
"Paris Oikonomou",
"Athanasios Dometios",
"Mehdi Khamassi",
"Costas S. Tzafestas",
"Paris Oikonomou",
"Athanasios Dometios",
"Mehdi Khamassi",
"Costas S. Tzafestas"
] | In this paper we introduce a novel technique that aims to dynamically control a two-module bio-inspired soft-robotic arm in order to qualitatively reproduce a path defined by sparse way-points. The main idea behind this work is based on the assumption that a complex trajectory may be derived as a combination of a discrete set of parameterizable simple movements, as suggested by Movement Primitive ... |
Constant Fluidic Mass Control for Soft Actuators Using Artificial Neural Network Algorithm | https://ieeexplore.ieee.org/document/9636630/ | [
"Heng Xu",
"Priyanshu Agarwal",
"Benjamin Stephens-Fripp",
"Heng Xu",
"Priyanshu Agarwal",
"Benjamin Stephens-Fripp"
] | Soft fluidic actuators are increasingly being used for wearable haptic devices due to their high energy density and low encumbrance. These actuators are typically controlled using constant fluidic pressure control (CFPC), where the actuator pressure is switched between a high pressure source and atmospheric pressure using a fluidic valve. However, this type of control has several limitations for s... |
A Soft Somesthetic Robotic Finger Based on Conductive Working Liquid and an Origami Structure | https://ieeexplore.ieee.org/document/9636431/ | [
"Junhwi Cho",
"Kyungseo Park",
"Hwayeong Jeong",
"Jung Kim",
"Junhwi Cho",
"Kyungseo Park",
"Hwayeong Jeong",
"Jung Kim"
] | The tactile and proprioceptive sensation increases human manipulability, and soft tissue compliance stabilizes the grasping function. However, it is challenging to transpose this system to the small confined space of soft robotic fingers due to the material properties and complex wiring entailed. Furthermore, soft robotic fingers also incorporate actuating components, making such a system more dif... |
Extended Tactile Perception: Vibration Sensing through Tools and Grasped Objects | https://ieeexplore.ieee.org/document/9636677/ | [
"Tasbolat Taunyazov",
"Luar Shui Song",
"Eugene Lim",
"Hian Hian See",
"David Lee",
"Benjamin C.K. Tee",
"Harold Soh",
"Tasbolat Taunyazov",
"Luar Shui Song",
"Eugene Lim",
"Hian Hian See",
"David Lee",
"Benjamin C.K. Tee",
"Harold Soh"
] | Humans display the remarkable ability to sense the world through tools and other held objects. For example, we are able to pinpoint impact locations on a held rod and tell apart different textures using a rigid probe. In this work, we consider how we can enable robots to have a similar capacity, i.e., to embody tools and extend perception using standard grasped objects. We propose that vibro-tacti... |
AuraSense: Robot Collision Avoidance by Full Surface Proximity Detection | https://ieeexplore.ieee.org/document/9635919/ | [
"Xiaoran Fan",
"Riley Simmons-Edler",
"Daewon Lee",
"Larry Jackel",
"Richard Howard",
"Daniel Lee",
"Xiaoran Fan",
"Riley Simmons-Edler",
"Daewon Lee",
"Larry Jackel",
"Richard Howard",
"Daniel Lee"
] | Perceiving obstacles and avoiding collisions is fundamental to the safe operation of a robot system, particularly when the robot must operate in highly dynamic human environments. Proximity detection using on-robot sensors can be used to avoid or mitigate impending collisions. However, existing proximity sensing methods are orientation and placement dependent, resulting in blind spots even with la... |
A Low-Cost Modular System of Customizable, Versatile, and Flexible Tactile Sensor Arrays | https://ieeexplore.ieee.org/document/9635851/ | [
"Niklas Fiedler",
"Philipp Ruppel",
"Yannick Jonetzko",
"Norman Hendrich",
"Jianwei Zhang",
"Niklas Fiedler",
"Philipp Ruppel",
"Yannick Jonetzko",
"Norman Hendrich",
"Jianwei Zhang"
] | The key role of tactile sensing for human grasping and manipulation is widely acknowledged, but most industrial robot grippers and even multi-fingered hands are still designed and used without any tactile sensors. While the basic design principles for resistive or capacitive sensors are well known, several factors keep tactile sensing from large-scale deployment — high sensor costs, short lifespan... |
Self-Contained Kinematic Calibration of a Novel Whole-Body Artificial Skin for Human-Robot Collaboration | https://ieeexplore.ieee.org/document/9636493/ | [
"Kandai Watanabe",
"Matthew Strong",
"Mary West",
"Caleb Escobedo",
"Ander Aramburu",
"Krishna Chaitanya Kodur",
"Alessandro Roncone",
"Kandai Watanabe",
"Matthew Strong",
"Mary West",
"Caleb Escobedo",
"Ander Aramburu",
"Krishna Chaitanya Kodur",
"Alessandro Roncone"
] | In this paper, we present an accelerometer-based kinematic calibration algorithm to accurately estimate the pose of multiple sensor units distributed along a robot body. Our approach is self-contained, can be used on any robot provided with a Denavit-Hartenberg kinematic model, and on any skin equipped with Inertial Measurement Units (IMUs). To validate the proposed method, we first conduct extens... |
A Multi-Chamber Smart Suction Cup for Adaptive Gripping and Haptic Exploration | https://ieeexplore.ieee.org/document/9635852/ | [
"Tae Myung Huh",
"Kate Sanders",
"Michael Danielczuk",
"Monica Li",
"Yunliang Chen",
"Ken Goldberg",
"Hannah S. Stuart",
"Tae Myung Huh",
"Kate Sanders",
"Michael Danielczuk",
"Monica Li",
"Yunliang Chen",
"Ken Goldberg",
"Hannah S. Stuart"
] | We present a novel robot end-effector for gripping and haptic exploration. Tactile sensing through suction flow monitoring is achieved with a new suction cup design that contains multiple chambers for air flow. Each chamber connects with its own remote pressure transducer, which enables both absolute and differential pressure measures between chambers. By changing the overall vacuum applied to thi... |
A Multi-Axis FBG-Based Tactile Sensor for Gripping in Space | https://ieeexplore.ieee.org/document/9635998/ | [
"Samuel Frishman",
"Julia Di",
"Zulekha Karachiwalla",
"Richard J. Black",
"Kian Moslehi",
"Trey Smith",
"Brian Coltin",
"Bijan Moslehi",
"Mark R. Cutkosky",
"Samuel Frishman",
"Julia Di",
"Zulekha Karachiwalla",
"Richard J. Black",
"Kian Moslehi",
"Trey Smith",
"Brian Coltin",
"Bijan Moslehi",
"Mark R. Cutkosky"
] | Tactile sensing can improve end-effector control and grasp quality, especially for free-flying robots where target approach and alignment present particular challenges. However, many current tactile sensing technologies are not suitable for the harsh environment of space. We present a tactile sensor that measures normal and biaxial shear strains in the pads of a gripper using a single optical fibe... |
Feasibility of Remote Landmark Identification for Cricothyrotomy Using Robotic Palpation | https://ieeexplore.ieee.org/document/9636481/ | [
"Neel Shihora",
"Rashid Yasin",
"Ryan Walsh",
"Nabil Simaan",
"Neel Shihora",
"Rashid Yasin",
"Ryan Walsh",
"Nabil Simaan"
] | Cricothyrotomy is a life-saving emergency intervention that secures an alternate airway route after a neck injury or obstruction. The procedure starts with identifying the correct location (the cricothyroid membrane) for creating an incision to insert an endotracheal tube. This location is determined using a combination of visual and palpation cues. Enabling robot-assisted remote cricothyrotomy ma... |
Force feedback on hand rest function in master manipulator for robotic surgery | https://ieeexplore.ieee.org/document/9636632/ | [
"Solmon Jeong",
"Kotaro Tadano",
"Solmon Jeong",
"Kotaro Tadano"
] | In robotic surgeries employing the master-slave operation scheme, various haptic devices have been adopted as master manipulators. The main challenge of the haptic device is to contribute to a sensitive reaction to external forces for operators. Since force perception on fingertips is impaired by unstable entire hand condition, stable hand condition helps to improve force perception. This study pr... |
SurRoL: An Open-source Reinforcement Learning Centered and dVRK Compatible Platform for Surgical Robot Learning | https://ieeexplore.ieee.org/document/9635867/ | [
"Jiaqi Xu",
"Bin Li",
"Bo Lu",
"Yun-Hui Liu",
"Qi Dou",
"Pheng-Ann Heng",
"Jiaqi Xu",
"Bin Li",
"Bo Lu",
"Yun-Hui Liu",
"Qi Dou",
"Pheng-Ann Heng"
] | Autonomous surgical execution relieves tedious routines and surgeon’s fatigue. Recent learning-based methods, especially reinforcement learning (RL) based methods, achieve promising performance for dexterous manipulation, which usually requires the simulation to collect data efficiently and reduce the hardware cost. The existing learning-based simulation platforms for medical robots suffer from li... |
Analytical Tip Force Estimation on Tendon-driven Catheters Through Inverse Solution of Cosserat Rod Model | https://ieeexplore.ieee.org/document/9636560/ | [
"Amir Hooshiar",
"Amir Sayadi",
"Mohammad Jolaei",
"Javad Dargahi",
"Amir Hooshiar",
"Amir Sayadi",
"Mohammad Jolaei",
"Javad Dargahi"
] | Tip force estimation on continuum arms is of crucial clinical importance for catheter-based procedures, i.e., catheter-based ablation therapies. In this study, an analytical solution for force estimation based on inverse Cosserat rod modeling was proposed and validated. Initially, a previously validated Bezier-based shape interpolation was used to parameterize the deformation and the kinematics an... |
Towards Safe In Situ Needle Manipulation for Robot Assisted Lumbar Injection in Interventional MRI | https://ieeexplore.ieee.org/document/9636220/ | [
"Yanzhou Wang",
"Gang Li",
"Ka-Wai Kwok",
"Kevin Cleary",
"Russell H. Taylor",
"Iulian Iordachita",
"Yanzhou Wang",
"Gang Li",
"Ka-Wai Kwok",
"Kevin Cleary",
"Russell H. Taylor",
"Iulian Iordachita"
] | Lumbar injection is an image-guided procedure performed manually for diagnosis and treatment of lower back pain and leg pain. Previously, we have developed and verified an MR-Conditional robotic solution to assisting the needle insertion process. Drawing on our clinical experiences, a virtual remote center of motion (RCM) constraint is implemented to enable our robot to mimic a clinician’s hand mo... |
Learning to Share Autonomy Across Repeated Interaction | https://ieeexplore.ieee.org/document/9636748/ | [
"Ananth Jonnavittula",
"Dylan P. Losey",
"Ananth Jonnavittula",
"Dylan P. Losey"
] | Wheelchair-mounted robotic arms (and other assistive robots) should help their users perform everyday tasks. One way robots can provide this assistance is shared autonomy. Within shared autonomy, both the human and robot maintain control over the robot’s motion: as the robot becomes confident it understands what the human wants, it increasingly intervenes to automate the task. But how does the rob... |
Cooperative Assistance in Robotic Surgery through Multi-Agent Reinforcement Learning | https://ieeexplore.ieee.org/document/9636193/ | [
"Paul Maria Scheikl",
"Balázs Gyenes",
"Tornike Davitashvili",
"Rayan Younis",
"André Schulze",
"Beat P. Müller-Stich",
"Gerhard Neumann",
"Martin Wagner",
"Franziska Mathis-Ullrich",
"Paul Maria Scheikl",
"Balázs Gyenes",
"Tornike Davitashvili",
"Rayan Younis",
"André Schulze",
"Beat P. Müller-Stich",
"Gerhard Neumann",
"Martin Wagner",
"Franziska Mathis-Ullrich"
] | Cognitive cooperative assistance in robot-assisted surgery holds the potential to increase quality of care in minimally invasive interventions. Automation of surgical tasks promises to reduce the mental exertion and fatigue of surgeons. In this work, multi-agent reinforcement learning is demonstrated to be robust to the distribution shift introduced by pairing a learned policy with a human team me... |
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