Abstract

Stereo Visual Teach & Repeat (VT&R) is a system for long-range, autonomous route following in unstructured 3D environments. As this system relies on a passive sensor to localize, it is highly susceptible to changes in lighting conditions. Recent work in the optics community has provided a method to transform images collected from a three-channel passive sensor into color-constant images that are resistant to changes in outdoor lighting conditions. This paper presents a lighting-resistant VT&R system that uses experimentally trained color-constant images to autonomously navigate difficult outdoor terrain despite changes in lighting. We show through an extensive field trial that our algorithm is capable of autonomously following a 1km outdoor route spanning sandy/rocky terrain, grassland, and wooded areas. Using a single visual map created at midday, the route was autonomously repeated 26 times over a period of four days, from sunrise to sunset with an autonomy rate (by distance) of over 99.9%. These experiments show that a simple image transformation can extend the operation of VT&R from a few hours to multiple days.

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