Research on the path planning method for a robot cluster in emergency monitoring of environmental emergencies

With the rapid pace of economic development, environmental emergencies have entered a period characterized by a high incidence rate. In response to this trend, heterogeneous multi-robot collaborative emergency monitoring has emerged as an innovative model for environmental surveillance. The collaborative path planning of heterogeneous multi-robot clusters in complex and unknown scenarios serves as the fundamental basis and challenging aspect for achieving fast, efficient, and accurate emergency monitoring. In this study, we propose an novel model for emergency monitoring robot clusters that enables swift acquisition of scene information through effective information coordination. Furthermore, we employ particle swarm optimization (PSO) to globally assign tasks and accomplish node deployment. Additionally, we establish a path planning method based on genetic algorithm for multi-robot multitarget cooperative monitoring. Finally, the feasibility of both the proposed monitoring mode and path planning method is verified through MATLAB simulations. The approach presented herein significantly enhances the deployment efficiency of emergency monitoring sensors while reducing the overall processing time required during emergencies.