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research-article

A Novel Parameter Optimization Method for the Driving System of High-Speed Parallel Robots

[+] Author and Article Information
Xin-Jun Liu

The State Key Laboratory of Tribology & Institute of Manufacturing Engineering, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, ChinaBeijing Key Lab of Precision/Ultra-precision Manufacturing Equipments and Control, Tsinghua University, Beijing 100084, China
xinjunliu@tsinghua.edu.cn

Gang Han

The State Key Laboratory of Tribology & Institute of Manufacturing Engineering, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China
hangang_1990@126.com

Fugui Xie

The State Key Laboratory of Tribology & Institute of Manufacturing Engineering, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, ChinaBeijing Key Lab of Precision/Ultra-precision Manufacturing Equipments and Control, Tsinghua University, Beijing 100084, China
xiefg@mail.tsinghua.edu.cn

Qizhi Meng

The State Key Laboratory of Tribology & Institute of Manufacturing Engineering, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China
qizhi_meng@163.com

Sai Zhang

Robot Phoenix, Shandong 250000, China
sai.zhang@robotphoenix.com

1Corresponding author.

ASME doi:10.1115/1.4040028 History: Received November 08, 2017; Revised April 10, 2018

Abstract

Driving system parameters optimization, especially the optimal selection of specifications of motor and gearbox, is very important for improving high-speed parallel robots’ performance. A very challenging issue is parallel robots’ performance evaluation that should be able to illustrate robots’ performance accurately and guide driving system parameters optimization effectively. However, this issue is complicated by parallel robots’ anisotropic translational and rotational dynamic performance, and the multi-parameters of motors and gearboxes. In this paper, by separating the influence of translational and rotational degrees of freedom (DOFs) on robots’ performance, a new dynamic performance index is proposed to reflect the driving torque in instantaneous acceleration. Then the influence of driving system’s multi-parameters on robots’ driving torque in instantaneous acceleration and cycle time in continuous motion is investigated. Based on the investigation, an inertia matching index is further derived which is more suitable for minimizing the driving torque of parallel robots with translational and rotational DOFs. A comprehensive parameterized performance atlas is finally established. Based on this atlas, the performance of a high-speed parallel robot developed in this paper can be clearly evaluated and the optimal combination of motors and gearboxes can be quickly selected to ensure low driving torque and high pick-and-place frequency.

Copyright (c) 2018 by ASME
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