A Route Planning Method Based on Coverage Cells for the Large Area Coverage Scenarios of the Multi-Drone and Truck Collaborative System
Chengyuan Liang, Liang Lu, Weiguo Xiao, Bin Han · 2024
The multi-drone and truck collaborative system (mDTCS) represents an ideal solution for large-area coverage tasks. However, in the mDTCS large-area coverage scenarios, the truck route, the scheduling of drone takeoff and landing, and the drones' coverage paths are coupled, complicating the route planning of mDTCS. The existing planning methods of mDTCS rarely consider these coupling phenomena. This paper addresses the coupled route planning problem for the mDTCS large-area coverage scenarios. A decoupling approach based on coverage cells is proposed. By dividing the target areas using the group of coverage cells and solving the coverage path candidates for each sub-area, the coupled route planning problem is equivalently simplified into the route planning problem for cooperative truck and drone visits to sub-areas with the coverage path for each sub-area remaining to be selected from the candidates. And a planning algorithm based on adaptive large neighborhood search heuristic (ALNS) is designed to solve the decoupled problem, which includes a preliminary selection mechanism for the execution schemes of the insertion operators and a heuristic initial solution generation method. These methods enable the complete route planning for both the truck and drones in the mDTCS large-area coverage scenarios.