Robot manipulator self-identification for surrounding obstacle detection

被引：43

作者：

Wang, Xinyu ^{[1
,3
]}

Yang, Chenguang ^{[2
]}

Ju, Zhaojie ^{[4
]}

Ma, Hongbin ^{[1
,3
]}

Fu, Mengyin ^{[1
,3
]}

机构：

[1] Beijing Inst Technol, Sch Automat, Beijing 100081, Peoples R China

[2] Swansea Univ, Coll Engn, Swansea SA1 8EN, W Glam, Wales

[3] Beijing Inst Technol, State Key Lab Intelligent Control & Decis Complex, Beijing 100081, Peoples R China

[4] Univ Portsmouth, Sch Comp, Portsmouth, Hants, England

来源：

MULTIMEDIA TOOLS AND APPLICATIONS | 2017年 / 76卷 / 05期

基金：

英国工程与自然科学研究理事会;

关键词：

Manipulator self-identification; Superpixel; Collision prediction; Point cloud;

D O I：

10.1007/s11042-016-3275-8

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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 (R) sensor and the Baxter (R) robot have been performed to demonstrate the performance of the proposed algorithms.

引用

页码：6495 / 6520

页数：26

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