Imperial College London
Alternate

DrStefanLeutenegger

Faculty of Engineering, Department of Computing

Visiting Reader
 
 
 
//

Contact

 

s.leutenegger Website

 
 
//

Location

 

ACE ExtensionSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@unpublished{Wang:2020,
author = {Wang, Y and Funk, N and Ramezani, M and Papatheodorou, S and Popovic, M and Camurri, M and Leutenegger, S and Fallon, M},
publisher = {arXiv},
title = {Elastic and efficient LiDAR reconstruction for large-scale exploration  tasks},
url = {http://arxiv.org/abs/2010.09232v1},
year = {2020}
}
Download

RIS format (EndNote, RefMan)

TY  - UNPB
AB  - We present an efficient, elastic 3D LiDAR reconstruction framework which canreconstruct up to maximum LiDAR ranges (60 m) at multiple frames per second,thus enabling robot exploration in large-scale environments. Our approach onlyrequires a CPU. We focus on three main challenges of large-scalereconstruction: integration of long-range LiDAR scans at high frequency, thecapacity to deform the reconstruction after loop closures are detected, andscalability for long-duration exploration. Our system extends upon astate-of-the-art efficient RGB-D volumetric reconstruction technique, calledsupereight, to support LiDAR scans and a newly developed submapping techniqueto allow for dynamic correction of the 3D reconstruction. We then introduce anovel pose graph sparsification and submap fusion feature to make our systemmore scalable for large environments. We evaluate the performance using apublished dataset captured by a handheld mapping device scanning a set ofbuildings, and with a mobile robot exploring an underground room network.Experimental results demonstrate that our system can reconstruct at 3 Hz with60 m sensor range and ~5 cm resolution, while state-of-the-art approaches canonly reconstruct to 25 cm resolution or 20 m range at the same frequency.
AU  - Wang,Y
AU  - Funk,N
AU  - Ramezani,M
AU  - Papatheodorou,S
AU  - Popovic,M
AU  - Camurri,M
AU  - Leutenegger,S
AU  - Fallon,M
PB  - arXiv
PY  - 2020///
TI  - Elastic and efficient LiDAR reconstruction for large-scale exploration  tasks
UR  - http://arxiv.org/abs/2010.09232v1
UR  - http://hdl.handle.net/10044/1/83886
ER  -
Download