A Coupling Algorithm for Task and Path Planning of Multi-UGVs under Environmental Inspiration

The Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) is a representative model for multi-UGVs task planning. It describes the allocation for tasks of several unmanned vehicles, considering the capacity of each vehicle and the requirements, as well as the time windows, of various tasks. However, existing studies primarily focus on the task assignment and do not consider the connection between path costs and obstacles in complicated scenarios. In this paper, we propose a coupled task and path planning algorithm for multiple unmanned vehicles under environmental inspiration. We introduces a novel path cost function and achieve seamless integration of solutions from the task level to the path level. Experimental results indicate that, in static obstacle environments, our algorithm module can provide more accurate task assignment and path planning results with smaller costs under similar time consumption.