Abstract
The end-effector pose accuracy of industrial robots is an important factor influencing their work performance. At present, laser tracker is one of the most popular instruments for position measurement of industrial robots. However, it is more difficult for orientation measurement. Considering the importance of robot’s orientation accuracy, this paper presents an orientation measurement method for industrial robots based on laser tracker. Firstly, an additional device with only one spherically mounted reflector (SMR), which has automatic movement function, is designed to measure the orientation of the robot’s end-effector. The mounting parameters can be obtained based on the spatial geometric invariance, combining the Lie group theory and the least squares method. And then the orientation information can be calculated by multiplying the rotation transformation matrix. An orientation measurement and compensation experiment was conducted on a 6-DOF industrial robot. It was found that the presented method can reduce the human errors made by manual operation and improve the measurement accuracy and efficiency, and it is simpler and easier to operate without establishing the base coordinate system. The experiment results showed that the mean orientation accuracy of robot’s end-effector was increased by more than 86.11% after compensation. Therefore, the orientation measurement method presented in this study is sensible and efficient, and could be used for the error compensation of robots to improve their accuracy.
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Acknowledgements
This work was supported by the Science and Technology Project of Guangzhou (No. 202201010072), the Higher Education Teaching Research and Reform Project of Guangdong Province (No. x2jq-C9213027), the National Natural Science Foundation of China (No. 51805172), and the Guangdong Basic and Applied Basic Research Foundation (No. 2019A1515011515).
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He, Z., Zheng, H., Yuan, H., Zhang, X. (2023). An Orientation Measurement Method for Industrial Robots Based on Laser Tracker. In: Yang, H., et al. Intelligent Robotics and Applications. ICIRA 2023. Lecture Notes in Computer Science(), vol 14275. Springer, Singapore. https://doi.org/10.1007/978-981-99-6504-5_24
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DOI: https://doi.org/10.1007/978-981-99-6504-5_24
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