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Worker Robots that Learn from Mistakes


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A robot arm attempts to clear a cluttered table.

University of Leeds scientists are using automated planning and reinforcement learning to train a robot to find an object in a cluttered space and move it.

Credit: University of Leeds (U.K.)

Computer scientists at the University of Leeds in the U.K. are using the artificial intelligence techniques of automated planning and reinforcement learning to train a robot to find an object in a cluttered space and move it.

The goal is to develop robotic autonomy, a state in which the machine can assess the unique circumstances presented in a task and find a solution.

The main challenge is that in a confined area, a robotic arm may not be able to grasp an object from above, and instead must plan a sequence of moves to reach the target object in a way that allows it to grasp the object.

Said Leeds researcher Wissam Bejjani, "Our work is significant because it combines planning with reinforcement learning. A lot of research to try and develop this technology focuses on just one of those approaches."

From University of Leeds (U.K.)
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Abstracts Copyright © 2019 SmithBucklin, Washington, DC, USA


 

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