【摘要】 为了进一步提升基于人工蜂群(artificial bee colony,ABC)算法机器人路径规划的科学性,文章在建立路径规划实验模型基础上在ABC算法中引入了混沌映射产生初始解和反轮盘赌机制进行并行选择,提出等距分布式并行搜索,同时在全局更新机制中引入势场作用,进而得到了一种改进人工蜂群的(improved artificial bee colony,IABC)算法。将IABC算法应用于路径规划,并利用Taguchi正交试验选取实验参数值与目标函数参数值进行基于ABC算法与IABC算法的路径规划对比实验,实验结果表明,IABC算法规划出的路径质量较佳,能够提升规划效率。更多还原

【Abstract】 In order to further improve the efficiency and path quality of robot path planning based on artificial bee colony(ABC) algorithm, an improved artificial bee colony(IABC) algorithm is proposed. Firstly, the experimental model of path planning is established. Then the ABC algorithm is improved. The chaotic map is introduced into the initial solution, and the anti-roulette mechanism is introduced to have a parallel selection. The equidistant distributed parallel search is presented, and the potential field is introduced into the global updating mechanism. Finally, the IABC algorithm is applied to the path planning. And the Taguchi orthogonal test is adopted to select the experimental parameter value and the objective function parameter value, so that the path planning comparison experiment based on ABC algorithm and IABC algorithm is carried out. The experimental results show that the IABC algorithm has a better path quality and improves the planning efficiency.更多还原