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" Last year, PM stood on the sidelines at the RoboCup U.S. Open, as teams from across the country kicked it out robot-to-robot:  Elizabeth Sklar has driven 15 hours from New York to Atlanta with her soccer team in the back seat. She has spent months trying to instill the essentials of the &amp;quot;beautiful game&amp;quot; in her players-cooperation, anticipation and the fluid choreography of a team working together. But as game-time approaches, she&amp;#039;s worried about more basic skills. Will her players be able to see the ball? Will they know where they are on the field? Will they be able to walk? Sklar is a computer science professor at Columbia University, and her players are small robotic dogs called Aibos, sold as toys by Sony. Her team, the Metrobots, is here to compete against other four-dog teams in the RoboCup U.S. Open, hosted by Georgia Tech. Now, on a Sunday morning in May, the four vaguely Snoopy-like robots are ready to take the field against their first opponents, a team from the University of Texas. The idea of robotic dogs playing soccer against each other seems like an amusing novelty-and to some extent, it is. But the RoboCup tournament is also a serious research endeavor, spurring new developments in robotics in the same way that computer chess helped to focus artificial intelligence research in the 1980s and 1990s. The first RoboCup tournament was held in 1997, the same year that IBM&amp;#039;s Deep Blue finally beat chess grandmaster Garry Kasparov, and its stated goal is to &amp;quot;develop a team of fully autonomous humanoid robots that can win against the human world soccer championship team by the year 2050.&amp;quot; There is no remote control and no coaching from the sidelines. Each robot makes its own decisions while working with its teammates to achieve their common aim: attempting to nudge a golf-ball-size orange ball into the goal on a 13-foot by 20-foot field of green felt. After winning the coin toss, a Texas dog bumps the ball across the center line with his chest to begin the game. The Metrobots&amp;#039; response is disconcerting. Their three fielders scan their heads back and forth, searching in vain for the ball. Then they take a few steps in apparently random directions, stop, and scan again. Soon, two of their players have wandered off the field, earning 30-second penalties. Meanwhile, their goalie is standing absolutely motionless in the goal, apparently dead to the entreaties of Sklar and her teammates. After three minutes, a Texas dog taps a ball past the lifeless keeper to put Texas in the lead. By the end of the second 10-minute half, Texas has scored five unanswered goals.  The Metrobots take the setback in stride. &amp;quot;The joys of robots,&amp;quot; sighs Sklar&amp;#039;s husband Simon Parsons, a computer science professor at City University of New York and the co-leader of the team. &amp;quot;When they work, they work okay. But when they fail, they fail spectacularly.&amp;quot; In this case, the robots had two key failures: they had trouble recognizing the ball, and even when they did, they were too slow to get there. But now Sklar, Parsons and the three graduate students who have made the trip with them have four hours before their next game to fix the bugs in their computer program. The rules of the tournament demand that each team use identical off-the-shelf Aibo robots, with no modifications - except to their brains. The dogs come with a default &amp;quot;personality&amp;quot; from Sony loaded onto a small removable memory stick, recognizing commands such as &amp;quot;Good boy,&amp;quot; &amp;quot;Don&amp;#039;t do that,&amp;quot; and &amp;quot;Check e-mail.&amp;quot; Each team writes its own program to control the behavior of the dogs-teaching them how to kick the ball, how to recognize the net, and so on-and loads it onto the memory stick. &amp;quot;Everybody has the same hardware platform, so it becomes a software competition,&amp;quot; says U.S. Open organizer Tucker Balch of Georgia Tech. &amp;quot;But it&amp;#039;s a software competition in the real world.&amp;quot; For instance, the dogs have to be able to recognize the orange of the ball even if the lighting changes when the sun goes behind a cloud. At Columbia, Sklar spends most of her year thinking about how to coordinate the efforts of multiple &amp;quot;agents&amp;quot; not unlike the players on a soccer pitch. She and her peers tackles problems ranging from how to allocate time on a shared network printer to building rescue robots. Like soccer players, such robots need robust vision to help them navigate through burning buildings or piles of rubble. Teamwork is just as important. Researchers want robots scattered across a disaster area to pool their data to form a coherent picture of the evolving situation, and use the the information to mount a coordinated response. On the RoboCup field, team play depends on wireless communication between the dogs, using the same technology found in laptop computers. The robots pool information about where they think the ball is and decide which robot should chase the ball while the others cut to the net or drop back on defense. &amp;quot;What we&amp;#039;re trying to avoid is the Little League style of play, where everyone on the field runs after the ball,&amp;quot; Sklar says. But the strategies only work if the dogs can find the ball. It&amp;#039;s a skill the robots had mastered back in the lab, but the change in venue has created mischief. After their first game, Sklar and her teammates sprawl on the field with their laptop computers open, trying to correct the problem. Through a camera mounted in their snout, the dogs perceive each shade of color as a weighted combination of red, green and blue, but the exact combination depends on the lighting conditions. While moving to a new venue might be a trivial challenge for a human player, the different objects in the background and the slightly changed lighting conditions are enough to confuse the dogs&amp;#039; vision. The programmers, therefore, are fine-tuning what range of colors the dogs should identify as &amp;quot;ball&amp;quot; -a difficult task, since the lighting varies across the field, and since the free T-shirts given out by the competition sponsors are also orange. Adding to the team&amp;#039;s troubles, as it turns out, a human handler has accidentally loaded an outmoded version of the code that controls how the players walk-a Bad News Bears mistake that explains why they were so slow during the game. It&amp;#039;s akin to forgetting your starting lineup back at the hotel. Game 2, against host Georgia Tech, is a must-win for the Metrobots to avoid elimination. As the game begins, it becomes clear that the Metrobots goalie is no longer comatose. Instead, he rises on his hind legs and begins pumping his forelegs in the air. The Metrobots exchange puzzled glances. &amp;quot;Don&amp;#039;t look at me,&amp;quot; Parsons says. &amp;quot;I didn&amp;#039;t program that.&amp;quot; On the field, the dogs from both teams are seeing the ball, and chasing it vigorously - though once they get to the ball, it&amp;#039;s not clear they know where to go with it. As well as the ball, the dogs are also seeing a small boy whose orange T-shirt is close enough to the ground for them to confuse it with the ball. After three robots charge towards the sidelines where he is standing, the referee asks him to hide behind the barrier at the edge of the field. The game is still scoreless with three minutes left, when a Metrobots attacker charges towards a loose ball in the Georgia Tech crease and nudges it forward twice - then loses sight of the ball. For what seems like an eternity, the Metrobots attacker and the Georgia Tech defender stand facing each other, scanning for the ball, unaware that it sits a few inches away. On the sidelines, the two teams yell encouragement to their respective robots. Finally, to the disappointment of the home crowd, the attacking Aibo catches sight of the ball and noses it home for a 1-0 victory. Victory is sweet, but Sklar pauses only briefly to savor it. The Metrobots have a long night ahead of them trying to optimize their team&amp;#039;s performance for the next day&amp;#039;s games. Now that the dogs can see the ball, Sklar wants to make sure they can also see the goals and the colored posts that mark the corners of the field, so that they can figure out where they are. The other teams are tinkering too, and as a result the quality of play is increasing perceptibly as the tournament progresses. The next morning, the Metrobots win their first game of the day to qualify for the semi-finals, where they are eliminated by a team from Carnegie Mellon&amp;#039;s famed Robotics Institute. But their semi-final berth has guaranteed them a spot in the 2006 World Championships, and their robots have progressed more in three days of testing in the heat of competition than in the months of advance preparation. The American champion has yet to be crowned, however. On Tuesday morning, Carnegie Mellon takes the field against the University of Pennsylvania. Both teams have dominated their opponents with superior fundamentals like speed and vision. &amp;quot;Just like in human sports, teams that are faster or stronger will win,&amp;quot; says Dan Lee of the Penn team. &amp;quot;A group of pros that don&amp;#039;t communicate with each other will still kill a team of regular people.&amp;quot; Both teams in the final, though, are &amp;quot;pros,&amp;quot; so the game will depend on cooperation and strategy. Penn plays an aggressive style, with all three of its fielders charging over the center line when they have possession of the ball. Carnegie Mellon plays more cautiously, always leaving one robot back on defense, and using a distinctive sideways swipe of the head to knock the ball upfield. After fighting to a 1-1 tie in regulation, a Carnegie Mellon robot heads the ball past the sprawling Penn goalie to claim the championship in overtime. While the robots still made some questionable decisions that humans would easily have avoided, the lack of glaring malfunctions in the final game counts as an important step towards a team of robots that can beat the World Cup champs in 2050. &amp;quot;Simulating human intelligence is not about always doing the optimal thing, because even humans don&amp;#039;t do that,&amp;quot; notes one of the robotics researchers watching from the stands. &amp;quot;It&amp;#039;s about never doing something really stupid.&amp;quot; "^^<http://www.w3.org/2001/XMLSchema#string>
<http://www.popularmechanics.com/technology/robots/a5371/3051166/>