| With the success of Mars Pathfinder's Sojourner rover, a new era of planetary exploration has opened, with demand for highly capable mobile robots. These robots must be able to traverse long distances over rough, unknown terrain autonomously, under severe resource constraints. Much prior work in mobile robot path planning has been based on assumptions that are not truly applicable to navigation through planetary terrains. Based on the author's firsthand experience with the Mars Pathfinder mission, this work reviews issues which are critical for successful autonomous navigation of planetary rovers. No current methodology addresses all of these constraints. We next develop the sensor-based “Wedgebug” motion-planning algorithm. This algorithm is complete, correct, requires minimal memory for storage of its world model, and uses only on-board sensors, which are guided by the algorithm to efficiently sense only the data needed for motion planning, while avoiding unnecessary robot motion. The planner has the additional advantage of producing locally-optimal paths, and is suitable for robots with a field-of-view limited in both downrange and angular scope, for a variety of applications including planetary navigation. This work includes the proof of completeness and correctness of the Wedgebug algorithm, and in particular provides a corrected, detailed proof of a key result required for the proof of completeness of the Wedgebug algorithm (and for the TangentBug algorithm which inspired this approach). In addition, we extend this result to a broader class of environments. The implementation of a version of Wedgebug, called “RoverBug,” on the Rocky7 Mars Rover prototype at the Jet Propulsion Laboratory (JPL) is described, and experimental results from operation in simulated martian terrain are presented. |
