視覚と行動のend-to-end学習により経路追従行動をオンラインで模倣する手法の提案

― 実環境における経路選択機能の検証と学習時間の短縮化の検討 ―

抄録

The purpose of this study is to make a robot to acquire path-following behavior with fewer learning steps by end-to-end learning using camera images as input. Our past studies have proposed an online imitation method of path-following behavior of vision and action. We added a function to select a path so that the robot can move in any direction, and verified the effectiveness of the function in simulations. However, the number of learning steps increased significantly when we added the path selection function, and it was desired to reduce the number of learning steps for experiments in a real environment. Therefore, we propose two methods to reduce the number of learning steps and verify their effectiveness through experiments. Furthermore, we verify the validity of the methods through experiments using a real robot.