Abstract: To study the optimal task allocation strategy and path planning problem of ground vehicles and unmanned aerial vehicles(UAVs)in the inspection process, an improved adaptive large neighborhood search(IALNS)algorithm—a two-stage hybrid heuristic algorithm—was proposed. In the first stage, a clustering algorithm was used to divide the target nodes according to the different demand levels and distances of the nodes to be inspected. In the second stage, a hybrid heuristic algorithm was used to solve the route scheduling problem. Six new local optimization operators were added, and a node redistribution strategy was introduced. The cooperative hybrid route with the minimum cost for vehicles and UAVs was obtained after iterations. The proposed algorithm solutions and other algorithm solutions were tested and comparatively analyzed, and the experimental data showed that the IALNS algorithm had significant advantages in solving the vehicles-UAVs cooperative inspection problem.

Key words: path planning, vehicles-UAVs cooperative mode, clustering algorithm, adaptive large neighborhood search, local optimization