Vision Based Obstacle Detection and Path Planning for Planetary Rovers

M. Snorrason (Charles River Analytics), J. Norris, and Paul Backes (Jet Propulsion Laboratory)

Proceedings of SPIE, Vol 3693, AeroSense, Orlando, Fl (April, 1999)

NASA’s next generation Mars rovers are capable of capturing panoramic stereo imagery of their surroundings. Three-dimensional terrain maps can be derived from such imagery through stereo image correlation. While 3-D data is inherently valuable for planning a path through local terrain, obstacle detection is not fully reliable due to anomalies and noise in the range data. We present an obstacle-detection approach that first identifies potential obstacles based on color-contrast in the monocular imagery and then uses the 3-D data to project all detected obstacles into a 2-D overhead-view obstacle map where noise originating from the 3-D data is easily removed. We also developed a specialized version of the A* search algorithm that produces optimally efficient paths through the obstacle map. These paths are of similar quality as those generated by the traditional A*, at a fraction of the computational cost. Performance gains by an order of magnitude are accomplished by a two-stage approach that leverages the specificity of obstacle shape on Mars. The first stage uses depth-first A* to quickly generate a somewhat sub-optimal path through the obstacle map. The following refinement stage efficiently eliminates all extraneous way-points. Our implementation of these algorithms is being integrated into NASA’s award-winning Web-Interface for Telescience.

Path planned around automatically detected obstacles (left) and shown in WITS (right)

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