针对基本蚁群算法在机器人路径规划中盲目性大、效率低以及易陷入局部最优等缺陷,提出一种在蚁群算法中修改信息素初始值、改进全局信息素更新方式以及改进状态转移规则的移动机器人路径规划方案,在栅格环境下对移动机器人的路径规划进行仿真测试,仿真结果表明该方案能缩小最优路径的查询范围,降低发现最优路径所需的循环次数,有效提高最优路径的搜索效率,整体性能优于普通蚁群算法。
According to the basic ant colony algorithm in robot path planning in the blindness,lowefficiency and easily falls into the local optimum,this paper presents an modify pheromone initial value,improved global pheromone update,and improvement of state transition rules for mobile robot pathplanning method based ant colony algorithm,the simulation test for mobile robot path planning in gridenvironment,simulation results shows that the method can reduce the range of searching the optimal path,reduce cycle times to find the optimal path,improve the efficiency of the optimal path searchingeffectively,the overall performance is better than the conventional ant colony algorithm.