Mapping and planning under uncertainty in mobile robots with long-range perception

Pierre Sermanet, Raia Hadsell, Marco Scoffier, Urs Muller, Yann LeCun

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

Abstract

Recent advances in self-supervised learning have enabled very long-range visual detection of obstacles and pathways (to 100 meters or more). Unfortunately, the category and range of regions at such large distances come with a considerable amount of uncertainty. We present a mapping and planning system that accurately represents range and category uncertainties, and accumulates the evidence from multiple frames in a principled way. The system relies on a hyperbolic-polar map centered on the robot with a 200m radius. Map cells are histograms that accumulate evidence obtained from a self-supervised object classifier operating on image windows. The performance of the system is demonstrated on the LAGR off-road robot platform.

Original languageEnglish (US)
Title of host publication2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
Pages2525-2530
Number of pages6
DOIs
StatePublished - 2008
Event2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS - Nice, France
Duration: Sep 22 2008Sep 26 2008

Publication series

Name2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS

Other

Other2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
CountryFrance
CityNice
Period9/22/089/26/08

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Mapping and planning under uncertainty in mobile robots with long-range perception'. Together they form a unique fingerprint.

  • Cite this

    Sermanet, P., Hadsell, R., Scoffier, M., Muller, U., & LeCun, Y. (2008). Mapping and planning under uncertainty in mobile robots with long-range perception. In 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS (pp. 2525-2530). [4651203] (2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS). https://doi.org/10.1109/IROS.2008.4651203