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The International Journal of Advanced Manufacturing Technology

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29-12-2023 | ORIGINAL ARTICLE

Graphic-enhanced collision detection for robotic manufacturing applications in complex environments

Authors: Jing-Rong Li, Rui-Hui Xin, Qing-Hui Wang, Yue-Feng Li, Hai-Long Xie

Published in: The International Journal of Advanced Manufacturing Technology | Issue 7-8/2024

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Abstract

High-performance collision detection is the key to achieving automatic trajectory planning and secure motion control for industrial robots. However, most existing solutions reported thus far are difficult to guarantee computational accuracy and efficiency simultaneously when it comes to complex manufacturing environments. Therefore, this work presents a graphic-enabled collision detection method for robotic manufacturing applications in complex environments. With this method, a collision detection model that can be applied to arbitrarily complex polyhedrons is first established by using graphics depth peeling technology. A rapid collision detection algorithm utilizing a programmable graphics pipeline of GPU is developed. Then, the proposed collision detection model is extended to robotic manufacturing applications in complex environments. The effectiveness and practicality of the proposed method are verified through comparative simulation experiments, which have shown that the authors’ method can greatly improve the computational efficiency, robustness, and memory consumption when compared with the existing methods, showing great application potential in collision-free trajectory planning and motion planning for robotic manufacturing applications in complex environments.

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Title: Graphic-enhanced collision detection for robotic manufacturing applications in complex environments
Authors: Jing-Rong Li
Rui-Hui Xin
Qing-Hui Wang
Yue-Feng Li
Hai-Long Xie
Publication date: 29-12-2023
Publisher: Springer London
Published in: The International Journal of Advanced Manufacturing Technology / Issue 7-8/2024
Print ISSN: 0268-3768
Electronic ISSN: 1433-3015
DOI: https://doi.org/10.1007/s00170-023-12851-7

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