基于智能优化方法的工业机器人时间最优轨迹规划方法

A Time Optimal Trajectory Planning Method for Industrial Robots Based on Intelligent Optimization Methods

随着工业自动化进程的加速,工业机器人的轨迹规划问题愈发凸显其重要性。由于传统轨迹规划方法在时间最优性方面的局限性,本文致力于研究基于智能优化算法的工业机器人时间最优轨迹规划。本文阐述了轨迹规划的定义并建立了相应的数学模型。通过对比传统方法与智能优化算法,重点探讨了基于粒子群优化和蚁群优化的时间最优轨迹规划方法,分别描述了问题并提出了求解策略。研究结果显示,智能优化算法在提升工业机器人运动效率和精度方面具有显著优势。

With the acceleration of industrial automation,the trajectory planning problem of industrial robots has become increasingly important.Due to the limitations of traditional trajectory planning methods in terms of time optimality,this paper aims to study the time optimal trajectory planning of industrial robots based on intelligent optimization algorithms.This article elaborates on the definition of trajectory planning and establishes a corresponding mathematical model.By comparing traditional methods with intelligent optimization algorithms,this paper focuses on exploring time optimal trajectory planning methods based on particle swarm optimization and ant colony optimization.The problems are described and solution strategies are proposed.The research results show that intelligent optimization algorithms have significant advantages in improving the efficiency and accuracy of industrial robot motion.