Real-time adaptive o-road vehicle navigation and terrain classification

Urs A. Muller, Lawrence D. Jackel, Yann LeCun, Beat Flepp

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

Abstract

We are developing a complete, self-contained autonomous navigation system for mobile robots that learns quickly, uses commodity components, and has the added benefit of emitting no radiation signature. It builds on the au- Tonomous navigation technology developed by Net-Scale and New York University during the Defense Advanced Research Projects Agency (DARPA) Learning Applied to Ground Robots (LAGR) program and takes advantage of recent scientific advancements achieved during the DARPA Deep Learning program. In this paper we will present our approach and algorithms, show results from our vision system, discuss lessons learned from the past, and present our plans for further advancing vehicle autonomy.

Original languageEnglish (US)
Title of host publicationUnmanned Systems Technology XV
Volume8741
DOIs
StatePublished - 2013
EventUnmanned Systems Technology XV Conference - Baltimore, MD, United States
Duration: May 1 2013May 3 2013

Other

OtherUnmanned Systems Technology XV Conference
CountryUnited States
CityBaltimore, MD
Period5/1/135/3/13

Fingerprint

autonomous navigation
research projects
navigation
robots
roads
learning
Navigation
vehicles
Real-time
autonomy
commodities
Autonomous Navigation
lessons learned
Navigation System
Vision System
Navigation systems
Autonomous Systems
Mobile Robot
Mobile robots
Signature

Keywords

  • Continuous real-time learning
  • Intelligent systems
  • Machine learning
  • Off-road autonomous vehicle navigation
  • Self learning system
  • Sharing learned knowledge between systems
  • Vision-based passive long range sensing

ASJC Scopus subject areas

  • Applied Mathematics
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics

Cite this

Muller, U. A., Jackel, L. D., LeCun, Y., & Flepp, B. (2013). Real-time adaptive o-road vehicle navigation and terrain classification. In Unmanned Systems Technology XV (Vol. 8741). [87410A] https://doi.org/10.1117/12.2015533

Real-time adaptive o-road vehicle navigation and terrain classification. / Muller, Urs A.; Jackel, Lawrence D.; LeCun, Yann; Flepp, Beat.

Unmanned Systems Technology XV. Vol. 8741 2013. 87410A.

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

Muller, UA, Jackel, LD, LeCun, Y & Flepp, B 2013, Real-time adaptive o-road vehicle navigation and terrain classification. in Unmanned Systems Technology XV. vol. 8741, 87410A, Unmanned Systems Technology XV Conference, Baltimore, MD, United States, 5/1/13. https://doi.org/10.1117/12.2015533
Muller UA, Jackel LD, LeCun Y, Flepp B. Real-time adaptive o-road vehicle navigation and terrain classification. In Unmanned Systems Technology XV. Vol. 8741. 2013. 87410A https://doi.org/10.1117/12.2015533
Muller, Urs A. ; Jackel, Lawrence D. ; LeCun, Yann ; Flepp, Beat. / Real-time adaptive o-road vehicle navigation and terrain classification. Unmanned Systems Technology XV. Vol. 8741 2013.
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