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针对狭窄空间中机械臂的路径规划问题,提出一种改进型蚁群优化算法应用于机械臂的路径规划。通过对传统蚁群算法从概率分布的计算、最优路径二次优化、路径淘汰机制等方面进行改进,并使用Matlab软件进行仿真。对比改进前后算法的收敛效果,发现改进型蚁群算法的自组织性大大增强了系统的鲁棒性,能够明显提高机械臂在矿井等复杂环境下的适应能力。
In order to solve the problem of robot arm path planning in narrow space, an improved ant colony optimization algorithm is proposed for robot arm path planning. The traditional ant colony algorithm is improved from the calculation of probability distribution, the second optimization of optimal path, the path elimination mechanism and so on, and the simulation is carried out by Matlab software. Compared with the convergence effect before and after the improvement, it is found that the self-organization of the improved ant colony algorithm greatly enhances the system robustness and can significantly improve the adaptability of the manipulator in complex environments such as mines.