Energy‐Efficient Local Path Planning for Lunar Rovers Using Fuzzy Dynamic Window Approach

ABSTRACT With the increasing number of lunar exploration missions, particularly those targeting the lunar south pole, the path planning and obstacle avoidance technology of lunar rovers has become crucial. This study addresses local path planning challenges for rovers in the complex environment of the lunar surface by proposing a dynamic window approach (DWA) combined with fuzzy logic control and energy management. We adopt the A* algorithm to provide target points for the DWA to optimize the global navigation strategy of the lunar rover. We introduced fuzzy logic control to adjust the evaluation function's weights, allowing the rover to safely cope with changing terrain and environmental conditions. Additionally, we considered the energy management of the lunar rover, using a wheel‐soil interaction model to predict driving performance on different terrains and select more energy‐efficient paths. Based on the DEM with 1.5‐m resolution, this study conducted several sets of experiments with the proposed method and applied it to the Leibniz and Faustini crater region. The results indicate that the developed method increases the lunar rover's dynamic planning capability in complex situations and optimizes the energy consumption at the same time, which can provide technical support for future tasks of lunar scientific research.