基于改进萤火虫算法与动态窗口法融合的移动机器人动态路径规划

针对传统萤火虫算法无法有效躲避未知障碍物、收敛速度慢、易陷入局部最优等问题，对其进行了改进，并将其与动态窗口法相结合，从而提出了一种移动机器人动态路径规划新算法。通过三种策略对萤火虫算法进行了改进：首先，采用Skew Tent混沌映射产生混沌序列对萤火虫种群进行初始化，提高萤火虫算法的全局收敛速度；其次，引入自适应步长平衡萤火虫算法全局和局部最优；最后采用差分进化算法通过变异、交叉和选择操作加强萤火虫算法的搜索能力。然后将改进萤火虫算法与动态窗口法相结合，使移动机器人在全局最优路径的基础上进行实时动态路径规划，在能保证全局最优路径的基础上有效躲避未知障碍物。本文基于MATLAB进行了仿真，仿真结果验证了所提算法的有效性。

Dynamic Path Planning of Mobile Robot Based on Fusion of Improved Firefly Algorithm and Dynamic Window Approach

Aiming at the problems of traditional firefly algorithm, such as unable to effectively avoid unknown obstacles, slow convergence speed and easy to fall into local optimal, a new dynamic path planning algorithm for mobile robot was proposed by combining it with dynamic window approach. Three strategies were used to improve the firefly algorithm. First, Skew Tent chaos mapping was used to generate chaotic sequences to initialize the firefly population and improve the global convergence speed of the firefly algorithm. Secondly, the global and local optimizations of adaptive step size balance firefly algorithm are introduced. Finally, differential evolution algorithm is used to enhance the search ability of firefly algorithm through mutation, crossover and selection operation. Then the improved firefly algorithm is combined with the dynamic window approach, so that the mobile robot can perform real-time dynamic path planning on the basis of the global optimal path, and effectively avoid unknown obstacles on the basis of ensuring the global optimal path. The simulation is carried out based on MATLAB, and the simulation results verify the effectiveness of the proposed algorithm.