The article discusses a learning framework that allows robots to simulate their own kinematics and motor control just by observing their movements in a mirror-like manner. This self-learned simulation enables accurate motion planning and allows the robot to detect abnormalities and recover from damage. The authors argue that this type of self-awareness and adaptability is crucial for robots to function effectively in everyday tasks and environments. The learning framework eliminates the need for extensive real-world data collection and kinematic priors.

 

Publication date: 22 Nov 2023
Project Page: Not provided
Paper: https://arxiv.org/pdf/2311.12151

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