Paper
31 January 2020 Precision manufacture of aspheric optics by robot-based bonnet polishing
Bo Zhong, Wen-hui Deng, Xian-hua Chen, Nan Zheng
Author Affiliations +
Proceedings Volume 11427, Second Target Recognition and Artificial Intelligence Summit Forum; 114271Q (2020) https://doi.org/10.1117/12.2551855
Event: Second Target Recognition and Artificial Intelligence Summit Forum, 2019, Changchun, China
Abstract
The high-precision aspheric optics is difficult to achieve batch production because of its high complexity and cost in manufacturing process. Bonnet polishing is an efficient and precision polishing technology that has been widely used in aspheric optics manufacturing process. The existing aspheric bonnet polishing is mostly based on the five-axis CNC machine, but its cost is high. With the development of robot technology, it is a new, economical and effective attempt to combine robotic technology with bonnet polishing technology and apply it to manufacture the precision aspheric optics. In this paper, the research on robot-based bonnet polishing technology of aspheric optics is carried out. Firstly, the robotbased bonnet polishing equipment is introduced. Then, the control model of the robot-based bonnet polishing technology of aspheric optics is established. Finally, the aspheric polishing verification experiments are completed, and the good results are obtained. In this paper, the high-efficiency and high-precision manufacture of aspheric optics by robot-based bonnet polishing technology is realized, which greatly reduces the cost of aspheric precision manufacturing equipment, and provides a new technology choice for the high-precision, low-cost and batch production of aspheric optics.
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bo Zhong, Wen-hui Deng, Xian-hua Chen, and Nan Zheng "Precision manufacture of aspheric optics by robot-based bonnet polishing", Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 114271Q (31 January 2020); https://doi.org/10.1117/12.2551855
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