強化学習により獲得した行動モデルの自動切り替えによる未知の実環境での移動ロボットの自律走行

抄録

The purpose of study is autonomous mobile robot navigation in any unknown real environments. A proposed system is based on switching of action models according to situations around the mobile robot. Action models for predefined basic shapes are trained in advance by deep reinforcement learning. In addition, mobile robot selects suitable action model based on shapes around the robot. Autonomous robot navigation experiments were performed in two real environments that include the place mainly consisted of basic shapes and the other place including complicated shape. The results of the experiments are shown in this paper.