Planetary Mission Preplanning with Heading-Specific Slope and Distance from Shadow

Abstract

An actual route and terrain for a planetary rover can only be experienced while driving, but preplanning is invaluable to pre-determining route viability. Mission preplanning uses best prior data of terrain topology and lighting for this purpose. A prevailing technique is to compute magnitude of terrain slope at grid points by differentiating elevations of a digital elevation model. Mission planners then threshold on this slope map with a rover’s pitch limit to determine whether a location is navigable or not. Traditional grid planning then ensues. This approach is highly restrictive since rovers can side slope on terrain that they cannot climb by direct ascent. All directions other than principal slope can be traversed with less pitch, but incurring some rover side slope. To address the limitation of preplanning on a criterion of maximum slope, this thesis explores planning with consideration of directionality of slope. It accounts for angle of attack at a location, not just amplitude of maximum terrain slope at the location. If a rover approaches a terrain coordinate at the direction of steepest ascent, the pitch required to traverse is the maximum slope of terrain. The planner implemented in this research accounts for the rover’s direction of driving on terrain, not just magnitude of maximum terrain slope. Experiments of heading-specific slope planning involved simulated hill and crater terrain as well as lunar data of Nobile Crater. Waypoint destinations unobtainable with non-heading-specific slope planning were possible with heading-specific slope planning. In cases where both types of planning were successful, heading-specific slope planning resulted in a shorter or equal length routes.

Polar navigation poses challenges for solar-powered rovers due to grazing incidences of light. Current planning thresholds on illumination levels of coordinates and binarizes them as lit or unlit. Unlit nodes are then pruned. However, shadow existence and location can’t be precisely known due to illumination map uncertainties as well as shadow variance within map timescales. This research implements a distance from shadow constraint that buffers a lighting margin by specifying and computing a euclidean distance away from shadowed nodes. Experiments of distance from shadow restriction planning involved lunar data of Nobile Crater.