FARLAP: Fast Robust Localisation using Appearance Priors

/, News Feed/FARLAP: Fast Robust Localisation using Appearance Priors

This paper is concerned with large-scale localisation at city scales with monocular cameras. Our primary motivation lies with the development of autonomous road vehicles — an application domain in which low-cost sensing is particularly important. Here we present a method for localising against a textured 3-dimensional prior mesh using a monocular camera. We first present a system for generating and texturing the prior using a LIDAR scanner and camera. We then describe how we can localise against that prior with a single camera, using an information-theoretic measure of image similarity. This process requires dealing with the distortions induced by a wide-angle camera. We present and justify an interesting approach to this issue in which we distort the prior map into the image rather than vice-versa. Finally we explain how the general purpose computation functionality of a modern GPU is particularly apt for our task, allowing us to run the system in real time. We present results showing centimetre-level localisation accuracy through a city over six kilometres.

[bibtex key=”PascoeICRA2015″]