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Relatively Lazy: Indoor-Outdoor Navigation Using Vision and GNSS

2021-01-13 14:43:45
Benjamin Congram, Timothy D. Barfoot

Abstract

Visual Teach and Repeat (VT&R) has shown relative navigation is a robust and efficient solution for autonomous vision-based path following in difficult environments. Adding additional absolute sensors such as Global Navigation Satellite Systems (GNSS) has the potential to expand the domain of VT&R to environments where the ability to visually localize is not guaranteed. Our method of lazy mapping and delaying estimation until a path-tracking error is needed avoids the need to estimate absolute states. As a result, map optimization is not required and paths can be driven immediately after being taught. We validate our approach on a real robot through an experiment in a joint indoor-outdoor environment comprising 3.5km of autonomous route repeating across a variety of lighting conditions. We achieve smooth error signals throughout the runs despite large sections of dropout for each sensor.

Abstract (translated)

URL

https://arxiv.org/abs/2101.05107

PDF

https://arxiv.org/pdf/2101.05107.pdf


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