Optimal path planning utilizing dissipation function based on terrain elevation map for lunar rovers
Masafumi Saito, Kenichiro Nonaka, Kazuma Sekiguchi · 2017
For planetary rovers, a path planning with reduced risk is critical to realize safety and efficient locomotion on uneven terrain. To realize such locomotion, it is important to combine the local information observed by on-board sensors and global geometry obtained from, for example, satellites. In this research, we focus on a motion planning integrating these geometric information with two different levels of resolutions. In this research, we interpolate DEM data using low-order function and generate the cost map which indicates the error between interpolation function and grid data. The rover is navigated to avoid the area with large error where the elevation changes drastically. We present an avoidance method based on the dissipation function related to the map error. The rover can avoid the hazardous areas and move economically using the optimal calculation and the cost map. Through numerical simulations, we compare the proposed method with two generally known search algorithms in order to verify the superiority of the proposed method.