Jump to Content
  1. Oxford
  2. MPLS
  3. Eng. Sci.
  4. ORI

Estimation, Search, and Planning (ESP) Research Group

Into darkness: Visual navigation based on a lidar-intensity-image pipeline

Authors
  1. Timothy D. Barfoot
  2. Colin McManus
  3. Sean Anderson
  4. Hang Dong
  5. Erik Beerepoot
  6. Chi Hay Tong
  7. Paul Furgale
  8. Jonathan D. Gammell
  9. John Enright
Publication Date
Abstract

Visual navigation of mobile robots has become a core capability that enables many interesting applications from planetary exploration to self-driving cars. While systems built on passive cameras have been shown to be robust in well-lit scenes, they cannot handle the range of conditions associated with a full diurnal cycle. Lidar, which is fairly invariant to ambient lighting conditions, offers one possible remedy to this problem. In this paper, we describe a visual navigation pipeline that exploits lidar’s ability to measure both range and intensity (a.k.a., reflectance) information. In particular, we use lidar intensity images (from a scanning-laser rangefinder) to carry out tasks such as visual odometry (VO) and visual teach and repeat (VT&R) in realtime, from full-light to full-dark conditions. This lighting invariance comes at the price of coping with motion distortion, owing to the scanning-while-moving nature of laser-based imagers. We present our results and lessons learned from the last few years of research in this area.

Publication Details
Type
Abstract-Refereed Conference Paper
Conference
International Symposium on Robotics Research (ISRR)
Series
Springer Tracts in Advanced Robotics (STAR)
Volume
114
Location
Singapore
Pages
487–504
Digital Object Identifier DOI
10.1007/978-3-319-28872-7_28
Manuscript
Google Scholar Google Scholar
Google Scholar
BibTeX Entry
@inproceedings{barfoot_isrr13,
author = {Timothy D Barfoot and Colin McManus and Sean Anderson and Hang Dong and Erik Beerepoot and Chi Hay Tong and Paul Furgale and Jonathan D Gammell and John Enright},
title = {Into darkness: {Visual} navigation based on a lidar-intensity-image pipeline},
booktitle = {Proceedings of the International Symposium on Robotics Research ({ISRR})},
year = {2013},
volume = {114},
series = {Springer Tracts in Advanced Robotics ({STAR})},
pages = {487--504},
address = {Singapore},
month = {16--19 } # dec,
doi = {10.1007/978-3-319-28872-7_28},
}