Terrain-Aware Path Planning and Map Update for Mars Sample Return Mission

This work aims at developing an efficient path planning algorithm for the driving objective of a Martian day (sol) that can take into account terrain information for application to the proposed Mars Sample Return (MSR) mission. To prepare the planning process for one sol (i.e., with a limited time allocated to driving), a map of expected rover velocity over a chosen area is constructed, obtained by combining traversability classes, rock abundance and slope at that location. The planning phase starts offline by computing several potential paths that can be traversed in one sol (i.e., a few hours), which will later provide suitable options to the rover if replanning is necessary due to unexpected mobility difficulties. Online, the rover gains information about its environment as it drives and updates the map locally if major discrepancies are found. If an update is made, the remaining driving time along the different options is recalculated and the most efficient path is chosen. The online process is repeated until the rover has reached its daily goal. When simulated on different areas at Gusev Crater, Mars, the algorithm correctly captured changes of terrain initially not mapped, and rerouted the rover to a more efficient path when necessary, in which case it effectively complied with the time constraint to reach the goal.