期刊
ADVANCED ROBOTICS
卷 26, 期 16, 页码 1825-1840出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/01691864.2012.685259
关键词
collision detection; teaching and playback; force control; joint torque sensors; human safety
类别
资金
- Center for Autonomous Intelligent Manipulation under Human Resources Development Program for Convergence Robot Specialists (Ministry of Knowledge Economy) [NIPA-2011-C7000-1001-0003]
- Basic Science Research Program through the National Research Foundation of Korea (NRF)
- Ministry of Education, Science and Technology [2011-0001150]
- Ministry of Public Safety & Security (MPSS), Republic of Korea [H1502-12-1002] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
- National Research Foundation of Korea [2007-0056650] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Industrial and service robots often physically interact with humans, and thus, human safety during these interactions becomes significantly important. Several solutions have been proposed to guarantee human safety, and one of the most practical, efficient solutions is the collision detection using generalized momentum and joint torque sensors. This method allows a robot to detect a collision and react to it as soon as possible to minimize the impact. However, the conventional collision detection methods cannot distinguish between intended contacts and unexpected collisions, and thus they cannot be used during certain tasks such as teaching and playback or force control. In this paper, we propose a novel collision detection algorithm which can distinguish intended contacts and unexpected collisions. In most cases, the external force during a collision shows a noticeably faster rate of change than that during an intended contact, and using this difference, the proposed observer can distinguish one from the other. Several experiments were conducted to show that the proposed algorithm can effectively distinguish intended contacts and unexpected collisions. (c) 2012 Taylor & Francis and The Robotics Society of Japan
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