Robot trajectory planning for gear chamfer grinding based on multi-objective collaborative optimization and quintic B-spline interpolation algorithm

被引：0

作者：

Yongguo Zhu ^{[1
]}

Xin Wang ^{[2
]}

Xin YafeiWang ^{[3
]}

Huike Zhuo ^{[4
]}

Yuan Zhang ^{[1
]}

undefined Wan ^{[5
]}

机构：

[1] Nanchang HangKong University,Department of Aeronautical Manufacturing and Mechanical Engineering

[2] Jiangxi Vocational College of Mechanical & Electrical Technology,School of Mechanical Engineering

[3] COMAC Shanghai Aircraft Manufacturing Co.,Manufacturing Engineering Technology Center

[4] Ltd,Department of Mechatronic Engineering

[5] Jiangxi Vocational Technical College of Industry & Trade,Military Research Institute Intelligent Manufacturing Center

[6] Jiangxi Guoke Defence Group Co.,undefined

[7] Ltd,undefined

来源：

The International Journal of Advanced Manufacturing Technology | 2025年 / 138卷 / 9期

关键词：

Gear; Chamfer; Grinding; Robot; Trajectory planning; Multi-objective collaborative optimization;

D O I：

10.1007/s00170-025-15716-3

中图分类号：

学科分类号：

摘要：

In response to the shortcomings, such as the incomplete quantification of evaluation indexes for robot trajectory planning and the inadequate consideration of robot joint motion performance during the gear chamfer grinding process, a robot trajectory planning method is proposed based on multi-objective collaborative optimization and quintic B-spline interpolation. Firstly, the robot trajectory of the gear chamfer grinding is pre-planned based on the three-dimensional model of the gear, and the robot trajectory points are discretized for the gear chamfer grinding. Subsequently, a multi-objective weighted comprehensive evaluation model for the chamfer grinding trajectory is established to quantitatively assess the quality of the chamfer grinding trajectory. Secondly, a multi-objective collaborative genetic algorithm is proposed to solve the mathematical model of the chamfer grinding trajectory, obtaining the optimal solution set of trajectory points. Next, a quintic B-spline interpolation algorithm is used to obtain the characteristic points of the robot joint trajectory to improve the motion performance of the robot joints. Finally, a comprehensive optimization method using the multi-objective collaborative genetic algorithm and the quintic B-spline interpolation algorithm is proposed for the gear chamfer grinding trajectory and joint trajectory of the robot. Experiment results show that the comprehensive evaluation index of the grinding trajectory is significantly improved, and the stability of the robot’s motion start-stop is greatly enhanced by using the gear chamfer grinding robot trajectory planning method proposed in this paper.

引用

页码：4397 / 4414

页数：17