Uploaded May 2018 | Updated September 2026, 2 weeks ago
ICRA 2018 Spotlight Video
Interactive Session Wed AM Pod R.4
Authors: Cop, Konrad Piotr; Borges, Paulo Vinicius Koerich; Dubé, Renaud
Title: DELIGHT: An Efficient Descriptor for Global Localisation Using LiDAR Intensities
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.
ICRA 2018 Spotlight Video
Interactive Session Wed AM Pod R.4
Authors: Cop, Konrad Piotr; Borges, Paulo Vinicius Koerich; Dubé, Renaud
Title: DELIGHT: An Efficient Descriptor for Global Localisation Using LiDAR Intensities
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.
