Optimal Global Path Planning for Wheel-Legged Robot on Mountain Terrain

Nowadays, motion performance of Wheel-legged robots has been significantly improved, meanwhile, the work scenarios and mission requirements are becoming more and more extensive, which puts higher demands on their autonomous capabilities. In the wild mountain environment, both robot power and traveling safety are important factors affecting the operation. Moreover, the large amount of known digital elevation map (DEM) data information and weather forecast information makes it possible to evaluate the energy efficiency and movement safety. Therefore, in addition to solving the traditional path length minimization, it is necessary to define path optimality for these two parameters separately. In this paper, we propose a global planning strategy based on Downward Project A∗ (DOP-A∗) algorithm for wheel-legged robots, which realizes the decrease of energy consumption and meteorological threat successfully. The simulation results demonstrate that three different optimal paths are generated by utilizing different efficiency or meteorological threat weight.