Robot manipulator self-identification for surrounding obstacle detection

作者：Xinyu Wang, Chenguang Yang, Zhaojie Ju, Hongbin Ma, Mengyin Fu · 发表于：Multimedia Tools and Applications · 年份：2016 · DOI：10.1007/s11042-016-3275-8 · 被引用次数：52 · 研究领域：Robot Manipulation and Learning、Robotic Path Planning Algorithms、Robotic Mechanisms and Dynamics

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.