Abstract
With increasing demands on the surface quality of key components in the high-tech fields, ultra-precision polishing technology has received much attention in recent years. Among the numerous ultra-precision polishing technologies, robotic polishing has become the focus of research due to its low cost and high degree of freedom. In robot polishing, ensuring the smooth movement of the robot is an important and challenging issue. This paper presents an algorithm to optimize the smoothness of joint trajectories under variable feedrate conditions. Firstly, the algorithm employs redundant variables to represent the robot’s redundant degrees of freedom and selects those which satisfy the established robot motion performance indexes. Subsequently, a one-way graph composed of the selected redundant variables is utilized to derive the graph optimization results. Ultimately, the final results can be obtained using the least squares method. Through simulations and experiments, it is demonstrated that the proposed optimization method can effectively improve the smoothness of robot motion during the polishing process.
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This research is financed by the National Natural Science Foundation of China under Grant Nos. 52275451, 51905345, and the Shanghai Pujiang Talent Program under Grant No. 21PJD028.
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Wu, H., Li, Z., Wang, R., Luo, Z., Zhu, L. (2023). Smooth Joint Motion Planning for Robot Polishing by Redundancy Optimization. In: Yang, H., et al. Intelligent Robotics and Applications. ICIRA 2023. Lecture Notes in Computer Science(), vol 14272. Springer, Singapore. https://doi.org/10.1007/978-981-99-6480-2_35
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DOI: https://doi.org/10.1007/978-981-99-6480-2_35
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