基于蚁群优化算法的焊接机器人路径规划

Chenxu Duan, Pan Zhang
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引用次数: 1

摘要

由于焊接机器人在焊接作业中要遍历大量的焊接点,焊接路径的长度直接影响到自动线的工作时间和生产效率。针对传统路径规划方法不适合多目标点的问题,提出了一种基于蚁群优化算法的路径规划方法。首先采用网格法对机器人工作环境进行仿真,然后建立蚁群算法模型,最后通过算法收敛得到最优焊接路径。以最短的焊接路径为规划目标,在MATLAB软件中进行仿真实验。结果表明,该方法在迭代次数较少的情况下获得了最优的路径规划效果,验证了将蚁群算法应用于焊接机器人路径规划的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Path Planning for Welding Robot based on Ant colony Optimization Algorithm
Since welding robots have to traverse a large number of welding points during welding operations, the length of the welding path directly affects the working time and production efficiency of the automatic line. In respect to the problem that traditional path planning methods are not suitable for multi-target points, a path planning method based on ant colony optimization algorithm (ACO) is proposed. Firstly, the robot's working environment is simulated with the grid method, then the ACO algorithm model is established, and finally an optimal welding path is obtained through algorithm convergence. Taking the shortest welding path as the planning goal, the simulation experiment is carried out in MATLAB software. The results show that the method obtains the optimal path planning effect under the condition of a small number of iterations, and verifies the feasibility of applying the ACO algorithm to the path planning for welding robots.
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