Rover traverse-optimizing planner for multi-objective deployment scenarios

Currently, traverse/mission planning for deployed rovers (e.g., on Mars) requires planetary scientists to spend many hours in laborious surface terrain analysis, with the goal of minimizing some traverse aspects (e.g., distance) and maximizing others (e.g., smoothness). This is a largely manual process, and the results are at best functional compromises balancing the various potentially mutually exclusive optimization goals. The Rover Traverse Optimizing Planner (RTOP) introduced here is an automated system which generates optimized traverses using a multivariate stochastic optimization algorithm based on terrain data. RTOP makes it possible to quickly and accurately generate traverses optimized in numerous simultaneous constraints, such as: lowest number of deployment segments, shortest traverse based on 3D Euclidian distance measure, smoothest traverse with respect to terrain roughness, least altitude change, or any combination of these. Additional constraints which are supported by the terrain data can be added directly to the system. Waypoints (as well as avoidance points) can be assigned to each traverse, and numerous alternate (Pareto-optimal) traverses can be generated for each deployment scenario. Depending on ground-truth in-situ assessment of terrain data traversability by a deployed rover (e.g., Curiosity), RTOP allows for frequent replanning of traverses/missions.