煤矿救援机器人路径规划的蚁群优化算法

煤矿救援机器人执行救援任务时，需躲避水、火、障碍物等危险区域，提升了路径规划的难度，为此提出了煤矿救援机器人路径规划的蚁群优化算法。充分考虑煤矿救援机器人运行过程中的水、火、障碍物等分布，采用栅格法建立机器人路径规划的环境模型，确定栅格环境模型内机器人路径规划问题的目标函数，采用蚁群优化算法求解机器人路径规划问题的目标函数，通过改进信息素规则、限制信息素阈值以及改进转移概率3个方面优化蚁群算法，避免蚁群算法求解全局最优解时陷入局部最优。实例分析结果表明，该算法在满足收敛速度条件下有效规划煤矿救援机器人行驶路径，所规划路径的路径长度、转角数量以及危险度均为最优，为机器人安全作业提供理论依据。

Ant colony optimization algorithm for path planning of coal mine rescue robot

When coal mine rescue robot performs rescue tasks，it needs to avoid dangerous areas such as water，fire and obstacles，which improves the difficulty of path planning.Therefore，an ant colony optimization algorithm for path planning of coal mine rescue robot is proposed.Fully considering the distribution of water，fire and obstacles during the operation of coal mine rescue robot，the grid method is used to establish the environment model of robot path planning，determine the objective function of robot path planning problem in the grid environment model，and the ant colony optimization algorithm is used to solve the objective function of robot path planning problem.The ant colony algorithm is optimized in three aspects:limiting pheromone threshold and improving transition probability to avoid falling into local optimization when the ant colony algorithm solves the global optimal solution.The example analysis results show that the algorithm can effectively plan the travel path of coal mine rescue robot under the condition of meeting the convergence speed，and the path length，number of corners and risk degree of the planned path are optimal，which provides a theoretical basis for the safe operation of the robot.