Research on collision detection algorithm of multi-robot bonnet polishing system

Kun Qin; Zian Liu; Jianchun Liu

doi:10.1117/12.2579860

5 November 2020 Research on collision detection algorithm of multi-robot bonnet polishing system

Kun Qin, Zian Liu, Jianchun Liu

Proceedings Volume 11568, AOPC 2020: Optics Ultra Precision Manufacturing and Testing; 1156815 (2020) https://doi.org/10.1117/12.2579860
Event: Applied Optics and Photonics China (AOPC 2020), 2020, Beijing, China

Abstract

In a multi-robot bonnet polishing system, the mobile space between robots overlaps with each other, so collision detection is the premise of the safe and stable operation of the system. The sphere and capsule bounding boxes are used to simplify the model of the multi-robot bonnet polishing system, and the collision detection problem is transformed into the judgment of intersection among bounding boxes in the simplified model. The intersection of bounding boxes is preliminarily judged by the second projection method. The bounding box is projected into line segments. It avoids a lot of multiplication and square operation. If the projection line segments are not overlapped, the bounding box will not intersect. If the projection line segments are overlapped, the problem is transformed into the shortest distance solution from point to point, point to line and line to line. Using space geometry method to calculate the shortest distance between point and line segment. Using the method of transforming reference coordinate system to calculate the shortest distance between two line segment. Through the analysis of simulation software, compared with other algorithms, the average time consumed of the algorithm is reduced by 100%, and the detection efficiency is significantly improved. The algorithm can be better applied to multi-robot bonnet polishing system.

Citation Download Citation

Kun Qin, Zian Liu, and Jianchun Liu "Research on collision detection algorithm of multi-robot bonnet polishing system", Proc. SPIE 11568, AOPC 2020: Optics Ultra Precision Manufacturing and Testing, 1156815 (5 November 2020); https://doi.org/10.1117/12.2579860

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