A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK ...A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning.展开更多
针对静态二维环境下移动机器人全局路径规划问题,提出一种基于改进人工鱼群算法(IAFSA)和MAKLINK图的路径规划方法.该方法以Lorentzian函数和正态分布函数为视野和步长的自适应算子,引入指数递减惯性权重因子,能够提高AFSA算法的收敛速...针对静态二维环境下移动机器人全局路径规划问题,提出一种基于改进人工鱼群算法(IAFSA)和MAKLINK图的路径规划方法.该方法以Lorentzian函数和正态分布函数为视野和步长的自适应算子,引入指数递减惯性权重因子,能够提高AFSA算法的收敛速度和计算精度. MS (JoséLuis Esteves Dos Santos)算法结合IAFSA算法分步寻优,取IAFSA算法优化后的最优路径为全局最优路径,可以解决以往算法在MAKLINK图中只能求近似全局最优路径的问题.仿真实验结果表明了所提出改进算法方案的可行性和有效性.展开更多
文摘A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning.
基金Supported by National Natural Science Foundation of P.R.China(50275150)National Research Foundation for the Doctoral Program of Higher Education of P.R.China(20040533035)
文摘针对静态二维环境下移动机器人全局路径规划问题,提出一种基于改进人工鱼群算法(IAFSA)和MAKLINK图的路径规划方法.该方法以Lorentzian函数和正态分布函数为视野和步长的自适应算子,引入指数递减惯性权重因子,能够提高AFSA算法的收敛速度和计算精度. MS (JoséLuis Esteves Dos Santos)算法结合IAFSA算法分步寻优,取IAFSA算法优化后的最优路径为全局最优路径,可以解决以往算法在MAKLINK图中只能求近似全局最优路径的问题.仿真实验结果表明了所提出改进算法方案的可行性和有效性.
