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Trajectory planning of a 4-RR(SS)2 high-speed parallel robot

Published online by Cambridge University Press:  07 January 2022

Huipu Zhang
Affiliation:
School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Manxin Wang*
Affiliation:
School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Haibin Lai
Affiliation:
School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Junpeng Huang
Affiliation:
Lianyungang Screws Robot Technology Co., Ltd, Lianyungang 222062, China
*
*Corresponding author. E-mail: mxwang@njust.edu.cn

Abstract

The trajectory-planning method for a novel 4-degree-of-freedom high-speed parallel robot is studied herein. The robot’s motion mechanism adopts RR(SS)2 as branch chains and has a single moving platform structure. Compared with a double moving platform structure, the proposed parallel robot has better acceleration and deceleration performance since the mass of its moving platform is lighter. An inverse kinematics model of the mechanism is established, and the corresponding relationship between the motion parameters of the end-moving platform and the active arm with three end-motion laws is obtained, followed by the optimization of the motion laws by considering the motion laws’ duration and stability. A Lamé curve is used to transition the right-angled part of the traditional gate trajectory, and the parameters of the Lamé curve are optimized to achieve the shortest movement time and minimum acceleration peak. A method for solving Lamé curve trajectory interpolation points based on deduplication optimization is proposed, and a grasping frequency experiment is conducted on a robot prototype. Results show that the grasping frequency of the optimized Lamé curve prototype can be increased to 147 times/min, and its work efficiency is 54.7% higher than that obtained using the traditional Adept gate-shaped trajectory.

Type
Research Article
Copyright
© The Author(s), 2022. Published by Cambridge University Press

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