Many of the actions we are taking are as it were "automatically". Agree, when we walk down the street in a crowd of other people — we are not thinking about how and where to put his feet when walking, on a path to circumvent the obstacle, and with what force to push off to jump across a small puddle. But the robots are deprived of the bonus. They need clear algorithms, otherwise they just get confused. To teach the robot to navigate in a constantly changing situation and is called new development experts from MIT.
Engineers at mit are currently busy creating a program that could teach the robots not just to navigate in space, but also to consider a lot of factors that can affect the final result. As stated by one of the authors Andrei Barbu
"Now the artificial intelligence works in the following way: move is used continuously running the algorithm pads the way. After each step, he analyzes the situation, "figure out" all possible actions and chooses from them the most optimal. Therefore, even a thousand times passing the same route, the robot will do everything well, like many attempts ago. He's just not enjoying the experience."
In order to improve this statistic, researchers from the Massachusetts Institute of Technology complements algorithms of movement the new — "factor in the recognition of the environment." It should allow the robot to navigate as we do. During a series of tests using the new design, robotic mechanisms had to overcome the obstacle with other moving objects. And it was revealed that unlike the first time, follow the passage not only less were counted again, but used the already obtained information on previous "tours".
Well, the interesting thing here is that the new algorithm at MIT are developing not so much for robots, but for self-driving cars, because such behaviors will enable much more efficient to analyze the urban environment and in theory can make a self-driving car more safe. The press service of the University has said that the new technology will be applied in the new project of MIT and Toyota.
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