機械学習による移動ロボットナビゲーションの運動計画と制御：サーベイ
Motion Planning and Control for Mobile Robot Navigation Using Machine Learning: a Survey
移動ロボットのナビゲーションにおける運動計画・制御への機械学習の応用研究を、古典的手法との関係に基づいて分類し、課題と今後の方向性を整理したサーベイ論文。
著者: Xuesu Xiao, Bo Liu, Garrett Warnell, Peter Stone
分類: cs.RO
原文アブストラクト
Moving in complex environments is an essential capability of intelligent mobile robots. Decades of research and engineering have been dedicated to developing sophisticated navigation systems to move mobile robots from one point to another. Despite their overall success, a recently emerging research thrust is devoted to developing machine learning techniques to address the same problem, based in large part on the success of deep learning. However, to date, there has not been much direct comparison between the classical and emerging paradigms to this problem. In this article, we survey recent works that apply machine learning for motion planning and control in mobile robot navigation, within the context of classical navigation systems. The surveyed works are classified into different categories, which delineate the relationship of the learning approaches to classical methods. Based on this classification, we identify common challenges and promising future directions.
