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arXiv · 1801.10599

Modeling and Multi-objective Optimization of a Kind of Teaching Manipulator

Zhun Fan·Yugen You·Haodong Zheng·Guijie Zhu·Wenji Li·Shen Chen·Kalyanmoy Deb·Erik Goodman
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Abstract

A new kind of six degree-of-freedom teaching manipulator without actuators is designed, for recording and conveniently setting a trajectory of an industrial robot. The device requires good gravity balance and operating force performance to ensure being controlled easily and fluently. In this paper, we propose a process for modeling the manipulator and then the model is used to formulate a multi-objective optimization problem to optimize the design of the testing manipulator. Three objectives, including total mass of the device, gravity balancing and operating force performance are analyzed and defined. A popular non-dominated sorting genetic algorithm (NSGA-II-CDP) is used to solve the optimization problem. The obtained solutions all outperform the design of a human expert. To extract design knowledge, an innovization study is performed to establish meaningful implicit relationship between the objective space and the decision space, which can be reused by the designer in future design process.

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Zhun Fan, Yugen You, Haodong Zheng, Guijie Zhu, Wenji Li, Shen Chen, Kalyanmoy Deb, Erik Goodman. 2018-01-31. Modeling and Multi-objective Optimization of a Kind of Teaching Manipulator. https://arxiv.org/abs/1801.10599

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