Delight: An Efficient Descriptor for Global Localisation Using LiDAR Intensities
Konrad P Cop, Paulo V K Borges, Renaud Dubé
Abstract
Place recognition is a key element of mobile robotics. It can assist with the “wake-up” and “kidnapped robot” problems, where the robot position needs to be estimated without prior information. Among the different sensors that can be used for the task (e.g., camera, GPS, LiDAR), LiDAR has the advantage of operating in the dark and in GPS-denied areas. We propose a new method that uses solely the LiDAR data and that can be performed without robot motion. In contrast to other methods, our system leverages intensity information (as opposed to only range information) which is encoded into a novel descriptor of LiDAR intensities as a group of histograms, named DELIGHT. The descriptor encodes the distributed histograms of intensity of the surroundings which are compared using chi-squared tests. Our pipeline is a two-stage solution consisting of an intensity-based prior estimation and a geometry-based verification. For a map of 220k square meters, the method achieves localisation in around 3s with a success rate of 97%, illustrating the applicability of the method in real environments.
BibTeX
@inproceedings{icra2018_delightanefficie,
title = {Delight: An Efficient Descriptor for Global Localisation Using LiDAR Intensities},
author = {Konrad P Cop and Paulo V K Borges and Renaud Dubé},
booktitle = {ICRA 2018},
year = {2018}
}