TY - JOUR
AU - Rankin, Arturo L.
AB - Detecting negative obstacles (ditches, holes, wadis, and other depressions) is one of the most difficult problems in perception for unmanned ground vehicle (UGV) off-road autonomous navigation. One reason for this is that the width of the visible portion of a negative obstacle may only span a few pixels at the stopping distance for vehicle speeds UGV programs aspire to operate at (up to 50kph). The problem can be further compounded when negative obstacles are obscured by vegetation or when negative obstacles are embedded in undulating terrain. Because of the variety of appearances of negative obstacles, a multi-cue detection approach is desired. In previous nighttime negative obstacle detection work, we have described combining geometry based cues from stereo range data and a thermal signature based cue from thermal infrared imagery. Thermal signature is a powerful cue during the night since the interiors of negative obstacles generally remain warmer than surrounding terrain throughout the night. In this paper, we further couple the thermal signature based cue and geometry based cues from stereo range data for nighttime negative obstacle detection. Edge detection is used to generate closed contour candidate negative obstacle regions that are geometrically filtered to determine if they lie within the ground plane. Cues for negative obstacles from thermal signature, geometry-based analysis of range images, and geometry-based analysis of terrain maps are fused. The focus of this work is to increase the range at which UGVs can reliably detect negative obstacles on cross-country terrain, thereby increasing the speed at which UGVs can safely operate.
TI - Night-time negative obstacle detection for off-road autonomous navigation
JF - Proceedings of SPIE
DO - 10.1117/12.720513
DA - 2007-04-27
UR - https://www.deepdyve.com/lp/spie/night-time-negative-obstacle-detection-for-off-road-autonomous-kOr0mi34ag
SP - 656103
EP - 656103-12
VL - 6561
IS - 1
DP - DeepDyve
ER -