Mars Rover localization and path-planning based on LIDAR and ant colony optimization

This paper presents a novel method for Mars Exploration Rover (MER) localization and path-planning by means of the terrain data from the light radio detecting and radar (LIDAR) in the final descent phase. Firstly, the real 3D terrain data of landing area from LIDAR in probe body coordinate system is transformed into a topographic map of roving area in landing site coordinate system. The map is further quantized and processed to generate a hazard map corresponding with real craters and rocks, which will be downloaded to the MER navigation database. Then, a novel path-planning algorithm based on ant colony optimization (ACO) is presented. Goal-oriented behavior, inertial behavior and obstacle-following behavior are appended to every ant individual of ACO by means of the fusion of behavior weights. Moreover, the shortest path from landing point to the exploration site is optimized by the tight-rope algorithm on the base of the path-planning result of ACO. The method and software developed are tested by using simulating data and the validity of the path planning algorithm is testified by simulation.