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Improving Autonomous Rover Guidance in Round-Trip Missions Using a Dynamic Cost Map

Autonomous round trip missions arise as an interesting topic since ESA and NASA agreed to bring soil samples from Mars. This work proposes a new method to improve autonomous rover guidance for this kind of missions. It is focused on the use of dynamically updated cost maps that are used to plan the rover path for a round-trip. The main advantage of the proposed method is the use of gathered information by the rover during the traverse. So, the cost map is updated in two ways, the first one, related to the encountered obstacles, which are included within the cost map; and the second one that uses terrain features to assign different costs to different patches of a segmented terrain. The generated cost map is then used to plan the return path based on the previously obtained information from the rover. The proposed method has been validated first in a simulation environment with Software in the Loop. The implementation is finally validated by in-field testing in a Mars-like environment. Results show the return traverse is improved by means of the proposed method.