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Robot manipulator self-identification for surrounding obstacle detection

Xinyu Wang, Chenguang Yang, Zhaojie Ju, Hongbin Ma, Mengyin Fu

Multimedia Tools and Applications, Volume: 76, Issue: 5, Pages: 6495 - 6520

Swansea University Author: Chenguang Yang

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DOI (Published version): 10.1007/s11042-016-3275-8

Abstract

Obstacle detection plays an important role for robot collision avoidance and motion planning. This paper focuses on the study of the collision prediction of a dual-arm robot based on a 3D point cloud. Firstly, a self-identification method is presented based on the over-segmentation approach and the...

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Published in: Multimedia Tools and Applications
ISSN: 1380-7501 1573-7721
Published: 2017
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URI: https://cronfa.swan.ac.uk/Record/cronfa27019
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Abstract: Obstacle detection plays an important role for robot collision avoidance and motion planning. This paper focuses on the study of the collision prediction of a dual-arm robot based on a 3D point cloud. Firstly, a self-identification method is presented based on the over-segmentation approach and the forward kinematic model of the robot. Secondly, a simplified 3D model of the robot is generated using the segmented point cloud. Finally, a collision prediction algorithm is proposed to estimate the collision parameters in real-time. Experimental studies using the KinectⓇ sensor and the BaxterⓇ robot have been performed to demonstrate the performance of the proposed algorithms
College: Faculty of Science and Engineering
Issue: 5
Start Page: 6495
End Page: 6520

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