Seeing the Wood for the Trees: Reliable Localization in Urban and Natural Environments

Georgi Tinchev, S. Nobili, M. Fallon

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In this work we introduce Natural Segmentation and Matching (NSM), an algorithm for reliable localization, using laser, in both urban and natural environments. Current state-of-the-art global approaches do not generalize well to structure-poor vegetated areas such as forests or orchards. In these environments clutter and perceptual aliasing prevents repeatable extraction of distinctive landmarks between different test runs. In natural forests, tree trunks are not distinctive, foliage intertwines and there is a complete lack of planar structure. In this paper we propose a method for place recognition which uses a more involved feature extraction process which is better suited to this type of environment. First, a feature extraction module segments stable and reliable object-sized segments from a point cloud despite the presence of heavy clutter or tree foliage. Second, repeatable oriented key poses are extracted and matched with a reliable shape descriptor using a Random Forest to estimate the current sensor's position within the target map. We present qualitative and quantitative evaluation on three datasets from different environments - the KITTI benchmark, a parkland scene and a foliage-heavy forest. The experiments show how our approach can achieve place recognition in woodlands while also outperforming current state-of-the-art approaches in urban scenarios without specific tuning.
Original languageEnglish
Title of host publication2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Place of PublicationMadrid, Spain
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages8
ISBN (Electronic)978-1-5386-8094-0, 978-1-5386-8093-3
ISBN (Print)978-1-5386-8095-7
Publication statusPublished - 1 Oct 2018
Event2018 IEEE/RSJ International Conference on Intelligent Robots and Systems - Madrid, Spain
Duration: 1 Oct 20185 Oct 2018

Publication series

ISSN (Print)2153-0858
ISSN (Electronic)2153-0866


Conference2018 IEEE/RSJ International Conference on Intelligent Robots and Systems
Abbreviated titleIROS 2018
Internet address


  • feature extraction
  • geophysical image processing
  • image matching
  • image segmentation
  • robot vision
  • vegetation mapping
  • reliable localization
  • urban environments
  • natural environments
  • current state-of-the-art global approaches
  • structure-poor vegetated areas
  • orchards
  • environments clutter
  • repeatable extraction
  • distinctive landmarks
  • natural forests
  • tree trunks
  • foliage intertwines
  • planar structure
  • place recognition
  • feature extraction module segments
  • reliable object-sized segments
  • heavy clutter
  • foliage-heavy forest
  • urban scenarios
  • random forest
  • shape descriptor
  • Feature extraction
  • Vegetation
  • Three-dimensional displays
  • Forestry
  • Reliability
  • Clutter
  • Hidden Markov models


Dive into the research topics of 'Seeing the Wood for the Trees: Reliable Localization in Urban and Natural Environments'. Together they form a unique fingerprint.

Cite this