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Adaptive long range vision in unstructured terrain
2007
2007 IEEE/RSJ International Conference on Intelligent Robots and Systems
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A novel probabilistic online learning framework for autonomous off-road robot navigation is proposed. The system is purely vision-based and is particularly designed for predicting traversability in unknown or rapidly changing environments. It uses self-supervised learning to quickly adapt to novel terrains after processing a small number of frames, and it can recognize terrain elements such as paths, man-made structures, and natural obstacles at ranges up to 30 meters. The system is developed
doi:10.1109/iros.2007.4399622
dblp:conf/iros/ErkanHSBML07
fatcat:vhh6h3g6j5hlhgsue63kjvvcd4