Shortest Path Planning for Energy-Constrained Mobile Platforms Navigating on Uneven Terrains

Finding a shortest feasible path between two given locations is a common problem in many real-world applications. Previous studies have shown that mobile platforms would consume excessive energy when moving along shortest paths on uneven terrains, which often consist of rapid elevation changes. Mobile platforms powered by portable energy sources may fail to follow such paths due to the limited energy available. This paper proposes a new heuristic search algorithm called constraints satisfying A* (CSA* ) to find solutions to such resource constrained shortest path problems. When CSA^∗ is guided by admissible heuristics, it guarantees to find a globally optimal solution to a given constrained search problem if such a solution exists. When CSA^* is guided by consistent heuristics, it is optimally efficient over a class of equally informed admissible constrained search algorithms with respect to the set of paths expanded. Test results obtained using real terrain data verify the applicability of the proposed algorithm in shortest path planning for energy-constrained mobile platforms on uneven terrains.