基于改进蚁群算法的机器人三维路径规划

Robot 3D path planning based on improved ant colony algorithm

针对蚁群算法在机器人三维避障路径规划中收敛速度慢以及精度较低的缺陷,结合人工势场法强化目标路径的优点,引入人工势场法中目标点处的引力域,修改了蚁群算法的启发值参数。在原有蚁群算法的基础上,提出了吸引素概念,根据吸引素修改了原有信息素参数的更新规则,使得蚁群算法能更快的达到收敛。最后仿真结果表明,在相同工作环境下改进后蚁群算法达到最优适应度值所需迭代次数相较于改进前存在明显的缩短,同时最优适应度值也有一定的提升。

Aiming at the defects of slow convergence speed and low accuracy of ant colony algorithm in robot 3D path planning,combining the advantages of strengthening the target path in the artificial potential field method,introducing the gravitational field at the target point in the artificial potential field method,modified the heuristic parameter of ant colony algorithm.And on the basis of the original ant colony algorithm,put forward the concept of prime attraction,modified the update rules of the original pheromone parameters based on attractors,make the ant colony algorithm reach convergence faster.Finally,the simulation results show that in the same working environment,the number of iterations required for the improved ant colony algorithm to reach the optimal fitness value is significantly shorter than that before the improvement.