Elasto-geometrical error and gravity model calibration of an industrial robot using the same optimized configuration set |
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| Affiliation: | 1. School of Mechatronic Engineering, Harbin Institute of Technology, Harbin 150001, China;2. Department of Mechanical Engineering, The University of Hong Kong, Pokfulam, Hong Kong;1. College of Engineering and Physical Sciences, Aston University, Birmingham, B47ET, UK;2. Department of Mechanical Engineering, The University of Auckland, Auckland, 1010, New Zealand;3. Department of Mechanical and Aerospace Engineering, Case Western Reserve University, Cleveland, OH 44106, USA;4. Department of Production Engineering, KTH Royal Institute of Technology, Stockholm, Sweden;5. Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW), University of Stuttgart, Stuttgart, 70174, Germany;1. Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, Harbin University of Science and Technology, Harbin 150080, China;2. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA;3. Department of Production Engineering, KTH Royal Institute of Technology, 11428 Stockholm, Sweden;1. School of Mechanical Engineering, Shandong University, Jinan 250061, PR China;2. Key Laboratory of High Efficiency and Clean Mechanical Manufacture at Shandong University, Ministry of Education, Jinan 250061, PR China |
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| Abstract: | Position error is a significant limitation for industrial robots in high-precision machining and manufacturing. Efficient error measurement and compensation for robots equipped with end-effectors are difficult in industrial environments. This paper proposes a robot calibration method based on an elasto–geometrical error and gravity model. Firstly, a geometric error model was established based on the D-H method, and the gravity and compliance error models were constructed to predict the elastic deformation caused by the self-weight of the robot. Subsequently, the position error model was established by considering the attitude error of the robot flange coordinate system. A two-step robot configuration selection method was developed based on the sequential floating forward selection algorithm to optimize the robot configuration for calibrating the position error and gravity models. Then, the geometric error and compliance coefficient were identified simultaneously based on the hybrid evolution algorithm. The gravity model parameters were identified based on the same algorithm using the joint torque signal provided by the robot controller. Finally, calibration and compensation experiments were conducted on a KR-160 industrial robot equipped with a spindle using a laser tracker and internal robot data. The experimental results show that the robot tool center point error can be significantly improved by using the proposed method. |
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