山区应急供水装备路径规划系统设计与应用

Design and application of path planning system for emergency water supply equipment in mountainous areas

灾后救援保障中,应急供水扮演着至关重要的角色.然而,由于山区地形和地貌条件复杂多变,现场指挥调度尤为关键,关系着救援人员能否迅速展开保障装备进行应急供水作业.文中基于多智能体强化学习(multi-agent proximal policy optimization,MAPPO)算法进行了路径规划系统的设计,并进行了试验仿真验证,根据奖励图结果确认该路径规划系统的可行性,并实现系统运行可视化,证明该路径规划系统可以初步满足山区应急供水装备路径规划需求.在此基础上,结合Mask2Former图像分割模型优化山区应急供水装备路径规划系统,将地物信息输出结果和路径规划结果相结合,有效避免了单一路径规划算法在受到环境影响时结果波动较大的问题,提高了路径规划的鲁棒性和可靠性.将该路径规划系统集成至山区应急供水装备指挥平台,以解决山区应急供水路径规划问题,为山区应急供水装备的实际运行提供了有力支持.

In post-disaster rescue and relief assurance,emergency water supply plays a crucial role.However,due to the complex and changeable mountainous terrain and geomorphic conditions,on-site command and dispatch are particularly critical in determining whether rescue workers can quickly deploy support equipment for emergency water supply operations.Based on the multi-agent proximal policy optimization(MAPPO)algorithm,a path planning system was designed and experimental verification was conducted.The feasibility of the path planning system is confirmed according to the results of the reward diagram,and the system operation was visualized,demonstrating that the path planning system could preliminarily meet the requirements for path planning of emergency water supply equipment in mountainous areas.On this basis,Mask2Former′s image segmentation model was integrated to optimize the path planning system for mountainous area emergency water supply equipment.By combining the results of ground object information output with path planning results,significant fluctuations were avoided in the results of single path planning algorithms when affected by the environment,thereby enhancing the robustness and reliability of path planning.Integrating this path planning system into the command platform for mountainous area emergency water supply equipment solved the path planning issues in mountainous,providing strong support for the actual operation of emergency water supply equipment in mountainous regions.