Aerial-Ground Vehicle Path Coordination Algorithms for Monitoring Applications

This study concerns a multi-UAV path planning problem in concert with a known ground vehicle path. The environment is given as a grid map, where each cell is either a target, an obstacle or contains nothing (neutral). Respectively, each cell has a reward that is either positive, negative, or zero. The team of UAVs has to visit as many targets as possible under a given time span or distance constraint, to maximize the collected reward. More formally, this problem is a generalization of the Orienteering Problem (OP) and is NP-Hard. In addition, the inclusion of obstacle avoidance and area coverage introduces additional complications that the current literature has not readily addressed. We propose using a greedy heuristic based on the A* algorithm, which involves three stages (selection, insertion, and post-processing) to solve this problem. A large scale problem instance is generated and the results are presented for different variations of our proposed algorithm. For large problems with thousand of nodes, our algorithm was able to provide a feasible solution to the proposed problem within few minutes of computation time on a standard laptop.