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Learning Robot Objectives from Physical Human Interaction

When humans and robots work in close proximity, physical interaction is inevitable. Traditionally, robots treat physical interaction as a disturbance, and resume their original behavior after the interaction ends. A team of researchers from Rice University and UC Berkeley  argue that physical human interaction is informative - it is useful information about how the robot should be doing its task. Results from their user study suggest that learning from physical interaction leads to better robot task performance with less human effort.

Topics:
Automation Motion Control Robotics

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