Visual path following on a manifold in unstructured three-dimensional terrain

This paper describes the design and testing of a technique to enable long-range autonomous navigation using a stereo camera as the only sensor. During a learning phase, the rover is piloted along a route capturing stereo images. The images are processed into a manifold map of topologically-connected submaps that may be used for localization during an autonomous repeat traverse. Path following in non-planar terrain is handled by moving from localization in three dimensions, to path following in two dimensions using a local ground plane associated with each submap. The use of small submaps decouples the computational complexity of route repeating from the length of the path. We validate the algorithm by demonstrating its performance on a difficult three-dimensional route. Using this technique, a rover may autonomously traverse a multi-kilometer route in unstructured, three-dimensional terrain, without an accurate global reconstruction.