Zeyu Li, Hongxing Wei, Chengguo Liu, Ye He, Gang Liu, Haochen Zhang, Weiming Li
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引用次数: 0
Abstract
Collaborative robots are becoming intelligent assistants of human in industrial settings and daily lives. Dynamic model identification is an active topic for collaborative robots because it can provide effective ways to achieve precise control, fast collision detection and smooth lead-through programming. In this research, an improved iterative approach with a comprehensive friction model for dynamic model identification is proposed for collaborative robots when the joint velocity, temperature and load torque effects are considered. Experiments are conducted on the AUBO I5 collaborative robots. Two other existing identification algorithms are adopted to make comparison with the proposed approach. It is verified that the average error of the proposed I-IRLS algorithm is reduced by over 14% than that of the classical IRLS algorithm. The proposed I-IRLS method can be widely used in various application scenarios of collaborative robots.
期刊介绍：
Robotica is a forum for the multidisciplinary subject of robotics and encourages developments, applications and research in this important field of automation and robotics with regard to industry, health, education and economic and social aspects of relevance. Coverage includes activities in hostile environments, applications in the service and manufacturing industries, biological robotics, dynamics and kinematics involved in robot design and uses, on-line robots, robot task planning, rehabilitation robotics, sensory perception, software in the widest sense, particularly in respect of programming languages and links with CAD/CAM systems, telerobotics and various other areas. In addition, interest is focused on various Artificial Intelligence topics of theoretical and practical interest.
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