Teaching a robot to use electric tools with regrasp planning

作     者：Mohamed Raessa Daniel Sánchez Weiwei Wan Damien Petit Kensuke Harada 

作者机构：School of Engineering ScienceOsaka UniversityOsakaJapan National Institute of Advanced Industrial Science and Technology(AIST)TsukubaJapan 

出 版 物：《CAAI Transactions on Intelligence Technology》 (智能技术学报（英文）)

年 卷 期：2019年第4卷第1期

页      面：54-63页

核心收录：

学科分类：0810[工学-信息与通信工程] 1205[管理学-图书情报与档案管理] 0839[工学-网络空间安全] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Japan Society for the Promotion of Science  JSPS  (17H01800) 

主　　题：electric tools regrasp planning 

摘      要：This study presents a straightforward method to teach robots to use tools.Teaching robots is crucial in quickly deploying and reconfiguring robots in next-generation factories.Conventional methods require third-party systems like wearable devices or complicated vision system to capture,analyse,and map human grasps,motion,and tool poses to robots.These systems assume lots of experience from their users.Unlike the conventional methods,this study does not involve learning human motion and skills.Instead,it only learns the object goal poses from the human user whilst employs regrasp planning to generate robot motion.The method is most suitable for a robot to learn the usage of electric tools that can be operated by simply switching on and off.The proposed method is validated using a dual-arm robot with hand-mounted cameras and several tools.Experimental results show that the proposed method is robust,feasible,and simple to teach robots.It can find a collision-free and kino-dynamic feasible grasp sequences and motion trajectories when the goal pose is reachable.The method allows the robot to automatically choose placements or handover considering the surrounding environment as intermediate states to change the pose of the tool and use tools following human demonstrations.