A Novel Navigation Beneficial Path Planning Algorithm for Application in Lunar Surface Exploration

The lunar south pole surface environment is characterized by sparse and homogeneous topographic features, poor optical texture and unstructured landforms, which brings great challenges to the lunar rover autonomous navigation. For high-precision autonomous navigation during lunar surface exploration, this paper proposes a novel path planning algorithm, the main purpose is to plan a travelable path that might be beneficial to improve the navigation accuracy. Firstly, the proposed method integrates the global auxiliary lines generated based on the A* algorithm into the Dynamic Window Approach (DWA). Then, a new cost function that takes into account the specialty of the lunar south pole environment and the accuracy impact factors of navigation is established. Finally, two kinds of simulations are conducted to verify the feasibility of the optimized path planning algorithm and whether it can improve the navigation accuracy. The simulation results indicated that the optimized path planning algorithm is more adaptable to complex environments and is effective in improving navigation accuracy.