基于改进蚁群算法的移动机器人火灾救援路径规划方法

为了解决在火灾救援中考虑多因素的移动机器人最优路径规划问题,提出一种基于改进蚁群算法的救援路径规划方法.通过改进全局信息素更新策略,考虑影响移动机器人到达待救援点时间的路径长度、转弯次数、坡度大小等主要因素,并根据多因素综合指标来分配各路径上的信息素量,指引蚂蚁走向最优路径.通过仿真算例并与同类方法对比,结果表明,该方法在考虑多因素后性能有较大提升,具有较好的全局搜索能力和收敛速度,可提高移动机器人在火灾救援中的效率.

Fire Rescue Path Planning Method of Mobile Robot Based on Improved Ant Colony Algorithm

In order to solve the problem of multi-factor optimal path planning for mobile robots in fire rescue, this paper proposes a rescue path planning method based on improved ant colony algorithm. While improving the global pheromone update strategy, it considered the main factors affecting the time for the mobile robot to reach the rescue point, such as the path length, the number of turns, and the size of the slope, and allocated the pheromone amount on each path according to the multi-factor comprehensive index, to guide the ant to the comprehensive optimal path. Through simulation examples and comparison with similar methods, the results show that the performance of the method in this paper is greatly improved after considering multiple factors, has better global search ability and convergence speed, and can improve the efficiency of mobile robots in fire rescue.