文献类型：期刊文献

英文题名：A Vision-Based Simultaneous Calibration Method for Dual-Robot Collaborative System

作者：Zhu, Lin[1];Cheng, Huayi[1];Yin, Xiaoqia[1];Zhang, Kaiming[1];Liu, Shuang[1];Zhang, Xiancheng[1]

机构：[1]East China Univ Sci & Technol, Sch Mech & Power Engn, Shanghai 200237, Peoples R China

年份：2024

卷号：20

期号：11

起止页码：13396

外文期刊名：IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS

收录：;EI(收录号：20244617364755);WOS:【SCI-EXPANDED(收录号:WOS:001288203700001)】；

基金：This work was supported in part by the National Key Research and Development Program of China under Grant 2022YFB4602102, in part by the National Natural Science Foundation of China under Grant 51975214, and in part by the Innovation Program Phase II of AECC Commercial Aircraft Engine Company Ltd. under Grant HT-3RJC1053-2020.

语种：英文

外文关键词：Calibration; Mathematical models; Collaboration; Robot sensing systems; Robots; Robot kinematics; Vectors; AXP(B) = YCPZ; dual-robot collaborative system; multiple coordinate frame; simultaneous calibration method

摘要：Dual-robot collaborative system has shown a significant potential for performing complex tasks. However, excellent interaction between cooperative manipulator involves a wide variety of coordinate frame transformations. Therefore, it is crucial for a dual-robot collaborative system to solve transformation relationships among the coordinate frames. In this article, a generalized matrix equation AXP(B) = YCPZ is formulated to described the kinematic transformation relationships in a dual-robot collaborative system. Furthermore, a novel vision-based simultaneous calibration method, consisting of a closed-form solution for estimation and an iterative optimization based on Lie algebra, was proposed for solving these unknown transformation matrices. It is worth that the proposed kinematic equation and calibration method only relies on the position information of the marker and provides greater versatility. Finally, in order to confirm the advancement of the proposed method, three mainstream methods are chosen for comparison. Relevant simulations and experiment demonstrate the novel calibration method provides great superiority in the accuracy, robustness, efficiency, and scenario compatibility, which can be applied to a variety of dual-robot collaboration tasks.