无人机多机协作探索煤矿灾变环境算法

针对目前煤矿灾变环境下救援机器人探索效率低的问题，提出了一种使用无人机多机协同探索煤矿灾变环境的改进型边界探索算法。该算法在效用值边界探索算法的基础上增加了对无人机导航角度因素的考虑，同时引入分散度函数作为评判机制来构建目标函数，并使用蚁群算法对该目标函数进行求解。最后利用Matlab软件在栅格化地图上进行了仿真实验。实验结果表明，和效用值边界探索算法相比，改进型边界探索算法减少了探测过程中的重复覆盖和拥挤现象，缩短了探测时间，降低了约30%的能量消耗，提高了无人机多机系统的整体探索效率。

Algorithm for exploring coal mine disaster environment by multi-UAV cooperation

Focusing on the low efficiency of the rescue robot in the coal mine disaster environment, a new improved boundary exploration algorithm based on multiple Unmanned Aerial Vehicles (multi-UAV) was proposed. Based on the utility value boundary exploration algorithm, the flight angle parameter of UAV was considered, and the distribution function was introduced as a judgment mechanism to construct the objective function. Finally, the ant colony algorithm was used to solve the objective function. Simulation experiments were carried out on a rasterized map with Matlab software. The simulation results show that the improved boundary exploration algorithm can reduce the phenomenon of repeated coverage and crowding, shorten the detection time, meanwhile the energy required by UAV is reduced by about 30%, thus improving the overall exploration efficiency of multi-UAV system.