1A2-K15 強化学習を用いた自律移動ロボットの環境適応に関する研究(宇宙ロボティクス・メカトロニクス)

概要

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An autonomous rover that is used as planetary exploration or rescue should work in unknown environment. Therefore, the rover needs to adapt to a new environment and should have to change its moving form. Therefore, a rover needs to judge situations around it, and should select the best action autonomously. This study aims at creating a rover which gets the best motion strategy for the environment or the action to recover from a stacked situation autonomously by using legs and wheels. For the adaptation method, we use a Reinforcement Learning scheme. To investigate availability of rover and to see the effect of learning, this study prepared virtual situations to escape from irregular ground as the experiments. As a result, the effectiveness of the method was shown. However, the result shows that the parameter largely effects over learning speed and the quality of solutions.
一般社団法人日本機械学会の論文
2011-05-26