考虑LIM栅格模型的MPMVPSO机器人路径规划算法

MPMVPSO Algorithm for Robot Path Planning Considering LIM Grid Model

为提高机器人路径规划算法精度,提出一种考虑局部交互机制(LIM)栅格模型的多种群多速度粒子群优化算法(MPMVPSO)的机器人路径规划方法。首先,对机器人路径规划的目标搜索过程,利用局部交互机制进行设计,考虑基于栅格法进行路径规划环境建模,该模型可基于启发式算法进行机器人路径规划过程优化;其次,引入粒子群优化算法,并通过全局最佳和局部最佳个体粒子进行进化个体引导,通过多种群多速度模型方式实现对粒子个体进化过程的优化,提升了粒子群优化算法性能;最后,与标准粒子群优化算法和现有改进粒子群优化算法进行对比实验,实验结果表明所提算法在机器人路径规划长度指标和计算效率指标上均要优于选取的对比算法,验证了算法有效性。

To improve the accuracy of robot path planning algorithm, a multi-population and multi-velocity particle swarm optimization(MPMVPSO) algorithm for robot path planning considering the grid model of local interaction mechanism(LIM) is proposed. Firstly, LIM is used to design the target search process of robot path planning, the path planning environment is modeled based on grid method, and the model can optimize robot path planning process based on heuristic algorithm. Secondly, particle swarm optimization algorithm is introduced, and evolutionary individual guidance is carried out through global and local optimal individual particles. And then, the evolutionary process of individual particles is optimized by the multi-population and multi-velocity model, which improves the performance of particle swarm optimization algorithm. Finally, by comparing with the standard particle swarm optimization algorithm and the existing improved particle swarm optimization algorithm, it shows that the proposed algorithm is superior to the selected comparison algorithms in terms of the length index and calculation efficiency index of robot path planning, which verifies the effectiveness of the algorithm.