Quadrotor-UAV Optimal Coverage Path planning in cluttered environment with a limited onboard energy

In this paper, a quadrotor optimal coverage planning approach in damaged area is considered. The quadrotor is assumed to visit a set of reachable points following the shortest path while avoiding the no-fly zones. The problem is solved by using a two-scale proposed algorithm. In the first scale, an efficient tool for cluttered environments based on optimal Rapidlyexploring Random Trees (RRT) approach, called multi-RRT* Fixed Node (RRT*FN), is developed to define the shortest paths from each point to their neighbors. Using the pair-wise costs between points provided by the firstscale algorithm, in the second scale, the overall shortest path is obtained by solving the Traveling Salesman Problem (TSP) using Genetic Algorithms (GA). Taking into consideration the limited onboard energy, a second alternative based on the well-known Vehicle Routing Problem (VRP) is used. This latter is solved using the savings heuristic approach. The effectiveness of this proposed two-scale algorithm is demonstrated through numerical simulations and promising results are obtained.