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提出了一种基于粒子群优化和极坐标变换的移动机器人路径规划方法,采用栅格法的极坐标和直角坐标变换关系对外部环境进行建模,利用粒子群优化算法建立了移动机器人的路径规划方法,指出了基于粒子群优化算法的移动机器人路径规划过程与马尔可夫链关系,并用概率论的方法分析了移动机器人路径规划方法的收敛性,阐明了本方法随均匀分布和正态分布的参数关系与收敛区间.仿真与计算结果证明了该方法对于移动机器人路径规划具有有效性与可行性.
A path planning method for mobile robot based on particle swarm optimization and polar coordinate transformation is proposed. The external environment is modeled by the grid transformation of polar coordinates and Cartesian coordinates. The particle swarm optimization algorithm is used to establish the path planning of mobile robot Method, the path planning process of the mobile robot based on Particle Swarm Optimization (PSO) is pointed out. The relationship between the path planning of the mobile robot and the Markov chain is pointed out. The convergence of the path planning method of the mobile robot is analyzed by the method of probability theory. Parameter relationship and convergence interval.The simulation and calculation results show that this method is effective and feasible for the path planning of mobile robots.