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research-article

Optimization Design of a Mobile Fixture Mechanism

[+] Author and Article Information
Xiao-Jin Wan

Hubei Key Laboratory of Advanced Technology of Automotive ComponentsHubei Collaborative Innovation Center for Automotive Components Technology, Wuhan University of Technology, Wuhan 430070, PR ChinaState Key Laboratory of Digital Manufacturing Equipment and Technology of China, Huazhong University of Science and Technology, Wuhan 430074, PR China
wxj_2001@163.com

Hanjie Zhang

Hubei Key Laboratory of Advanced Technology of Automotive ComponentsHubei Collaborative Innovation Center for Automotive Components Technology, Wuhan University of Technology, Wuhan 430070, PR China
15671562197@163.com

1Corresponding author.

ASME doi:10.1115/1.4039856 History: Received November 19, 2017; Revised March 21, 2018

Abstract

In this paper, a novel fixture mechanism with combining a mobility of the legged robot and advantages of parallel mechanism is designed to hold the different size and shape, large-scale workpiece. The proposed mobile fixture mechanism holds the workpiece as a parallel manipulator. While it walks as a legged robot. This kind of robotized fixtures can possess high self-configurable ability to accommodate a wider variety of products. In order to obtain the best kinematic dexterity and accuracy characteristics, comprehensive performance optimization is performed by non-dominated-genetic algorithm (NSGA-II). In the optimization procedure, a conventional kinematic transformation matrix (Jacobian matrix) and error propagation matrix are obtained through derivation and differential motion operations. The singular values and condition number based on velocity Jacobians and error amplification factors based on error propagation matrix are derived, in addition, relative pose error range of end-effector (EE) are also derived. On the basis of the above measure indices, three kinds of nonlinear optimization problems are defined to obtain the optimal architecture parameters for better kinematic accuracy and dexterity in workspace. Comparison analyses of the Optimized results are performed.

Copyright (c) 2018 by ASME
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