【作者】 王奇志； 徐德； 时鲁艳；

【Author】 QiZhi Wang1, De Xu2, Lu Yan Shi1 1 School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044,P.R.China2 State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences,Beijing 100190,P.R.China

【机构】 北京交通大学计算机与信息技术学院； 中国科学院自动化研究所复杂系统智能控制与管理国家重点实验室；

【摘要】 本文针对机器人的模仿学习与人机交互的学习控制方法进行综述,给出机器人学习控制的研究现状、分类方法以及最新的研究成果。针对模仿学习从定义、分类方法和控制策略分别加以论述。针对人机交互两种典型的交互方法进行重点阐述。更多还原

【Abstract】 Robots have been increasingly and significantly more powerful and intelligent over the last decade, and moving towards more service oriented roles. Imitation learning and human-robot interaction play important roles in effectively improving robot’s intelligence and ability to co-work with human being. This paper reviews the current state of the art in robot learning and controlling based on im itation learning and bum an-robot interaction. Recent research, classification method and new developm ents in this area are reviewed.Specifically the definition of action-based imitation,and the control strategy for imitation learning are addressed. Human-robot physical interaction and multi-modal interaction are emphasized.更多还原