基于改进A* 和内螺旋算法的林草火灾救援路径规划

在机器人奔赴火场的路径规划过程中，针对传统的A*算法在火灾救援过程中存在的遍历节点数和转弯次数过多的问题，提出改进的A*算法。该算法在启发函数中加入加权曼哈顿距离以提高算法的运行效率，引入惩罚函数和奖励因子减少机器人在火场奔赴过程中的转弯次数。到达火场后需要对该火场区域进行遍历，研究中基于火点热辐射原理，采用内螺旋算法对火场进行梯度式靠近，以减少高温对于巡检机器人运行性能的影响。仿真实验结果表明，与传统的A*算法相比，改进的A*算法可以有效减少奔赴火场过程中的遍历节点数和转弯次数，提高了巡检机器人的运行效率，在遍历火场的过程中，内螺旋算法可以以较高的覆盖率遍历火场区域。

Rescue path planning of forest and grass fire based on improved A* and inner spiral algorithm

In the path planning process of the robot going to the fire, aiming at the problems of too many traversed nodes and too many turns in the traditional A* algorithm in the fire rescue process, an improved A* algorithm is proposed, which adds weighting to the heuristic function. In order to improve the operating efficiency of the algorithm, the Manhattan distance is introduced, and the penalty function and reward factor are introduced to reduce the number of turns of the robot in the process of rushing to the fire field. After arriving at the fire field, it is necessary to traverse the fire field area. In the research, based on the principle of heat radiation at the fire point, the inner spiral algorithm is used to approach the fire field in a gradient manner to reduce the impact of high temperature on the operation performance of the inspection robot. The simulation results show that, compared with the traditional A* algorithm, the improved A* algorithm can effectively reduce the number of traversed nodes and the number of turns in the process of going to the fire field, and improve the operation efficiency of the inspection robot. During the process, the inner spiral algorithm can traverse the fire area with a high coverage rate.