Tiewu Xiang, Chunhui Gao, Baoan Du, Guifang Qiao, Hongfu Zuo
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引用次数: 0
Abstract
The problem of the insufficient accuracy performance of industrial robots in high-precision manufacturing is addressed in this paper. Firstly, a kinematic error model based on an M-DH model was presented. Secondly, a hybrid observability index O6 was proposed to select the optimal poses for parameter identification. O6 is the combination of O1 and O3. The optimal poses were obtained by using the IOOPS algorithm. Thirdly, the fitness function for parameter identification was established, and the Levenberg–Marquardt (LM) algorithm was applied for the accurate identification of kinematic parameter errors. Finally, several experiments were conducted to evaluate the performance of the proposed hybrid observability index O6. The average position error and average attitude error of Staubli TX60 robot were reduced by 89% and 49%. The results show that the proposed hybrid observability index O6 has great stability and effectiveness for robot calibration.
期刊介绍:
Machines (ISSN 2075-1702) is an international, peer-reviewed journal on machinery and engineering. It publishes research articles, reviews, short communications and letters. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. Full experimental and/or methodical details must be provided. There are, in addition, unique features of this journal: *manuscripts regarding research proposals and research ideas will be particularly welcomed *electronic files or software regarding the full details of the calculation and experimental procedure - if unable to be published in a normal way - can be deposited as supplementary material Subject Areas: applications of automation, systems and control engineering, electronic engineering, mechanical engineering, computer engineering, mechatronics, robotics, industrial design, human-machine-interfaces, mechanical systems, machines and related components, machine vision, history of technology and industrial revolution, turbo machinery, machine diagnostics and prognostics (condition monitoring), machine design.