Research on collision detection algorithm of robot arm based on multi-view object detection

Aiming at the difficult problem of collision detection in the trajectory planning process of the robotic arm in an unstructured environment, a multi-view object detection algorithm based on geometric collision detection and deep learning is proposed. Three global cameras are deployed in the robot wo...

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Vydáno v:Journal of physics. Conference series Ročník 3062; číslo 1; s. 12003 - 12009
Hlavní autoři: Hu, Xiangtao, Zhou, Fujie, Li, Ziyi, Wei, Zhihong
Médium: Journal Article
Jazyk:angličtina
Vydáno: Bristol IOP Publishing 01.07.2025
Témata:
Algorithms
Artificial neural networks
Barriers
Machine learning
Object recognition
Robot arms
Trajectory planning
Working conditions
ISSN:1742-6588, 1742-6596
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Shrnutí:Aiming at the difficult problem of collision detection in the trajectory planning process of the robotic arm in an unstructured environment, a multi-view object detection algorithm based on geometric collision detection and deep learning is proposed. Three global cameras are deployed in the robot working environment to ensure the integrity of the environmental observation. By pre-training Mask R-CNN, the obstacles in the observed image are detected, and the obstacle circular encircle box is constructed. The geometric collision detection model is used to determine the occupying relationship between the robot arm and the obstacle in the image plane. The test results in the simulation environment show that the proposed method not only has high detection accuracy but also fast detection efficiency, and realizes the collision detection of the robot arm in the unstructured environment.
Bibliografie:ObjectType-Article-1
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ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/3062/1/012003