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Research on Robot Path Planning Based on Improved Adaptive Ant Colony Algorithm

机译:基于改进的自适应蚁群算法的机器人路径规划研究

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Aiming at the problem that ant colony algorithm is easy to fall into local optimal and slow convergence in robot path planning, a path planning method based on improved ant colony algorithm is proposed for static obstacle environment.This method improves the search efficiency of the algorithm by using the adaptive adjustment heuristic function; The attenuation coefficient is adjusted dynamically to accelerate the convergence speed of the algorithm based on ant colony rule, pheromone is updated and the maximum and minimum of pheromone concentration is limited.Simulation results show that compared with other algorithms in the same environment, the improved algorithm has a faster convergence rate when the path planning results are the same.The improved algorithm has obtained the optimal path in different complexity environments, which also shows the effectiveness and reliability of the algorithm.
机译:针对机器人路径规划中蚁群算法容易陷入局部最优且收敛速度较慢的问题,提出了一种基于改进蚁群算法的静态障碍物路径规划方法,该方法提高了算法的搜索效率。使用自适应调整启发式函数;根据蚁群规则动态调整衰减系数以加快算法的收敛速度,更新信息素,限制信息素浓度的最大值和最小值。仿真结果表明,与相同环境下的其他算法相比,改进算法改进后的算法在不同复杂度的环境中获得了最优的路径,这也证明了算法的有效性和可靠性。

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