基于改进人工鱼群算法的机器人路径规划

Robot Path Planning Based on Improved Artificial Fish Swarm Algorithm

针对机器人全局路径规划中采用人工鱼群算法容易陷入局部最优,提出了一种混合改进人工鱼群算法(Hybrid Improved Artificial Fish Swarm Algorithm,HIAFSA)。首先,通过A*规划出次优路径确定人工鱼群规模;随后,鱼群算法中基于惯性权重因子的自适应行为,引入衰减函数α改进人工鱼的视野范围和移动步长,平衡算法全局路径规划和局部路径规划,进一步提高算法的收敛速度和解的质量。实验结果表明混合改进人工鱼群算法在避免局部最优、收敛速度和精度等方面都得到提高。

The artificial fish swarm algorithm is easy to fall into the local optimum for robot global path planning.A hybrid improved artificial fish swarm algorithm(HIAFSA)is proposed.Firstly,the sub-optimal path is determined by A*algorithm,and then the adaptive behavior based on the inertia weighting factor in the fish swarm algorithm is used to improve the visual field range and the moving step size of the artificial fish.The attenuation function balances the algorithm’s global path planning and local path planning,which further improves the algorithm’s convergence speed and solution quality.The experimental results show that the hybrid improved artificial fish swarm algorithm has been improved in avoiding local optimum,convergence speed and precision.