What is it about?
We develop a robot using a characteristic of the peristaltic crawling and drive the movement pattern of the robot by Actor-Critic which is one of the reinforcement learning. . Moreover, we indicated a provided movement pattern for a real robot and make a test run.
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Why is it important?
This study derived a movement pattern for application to a many-segmented peristaltic crawling robot using Actor–Critic. Q-learning was unable to perform calculations because of lack of memory, but Actor–Critic can derive the movement pattern algorithm of a many-segmented robot.
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This page is a summary of: Acquisition of earthworm-like movement patterns of many-segmented peristaltic crawling robots, International Journal of Advanced Robotic Systems, October 2016, SAGE Publications,
DOI: 10.1177/1729881416657740.
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