Adaptive long range vision in unstructured terrain

Ayse Naz Erkan; Raia Hadsell; Pierre Sermanet; Jan Ben; Urs Muller; Yann LeCun

doi:10.1109/IROS.2007.4399622

Adaptive long range vision in unstructured terrain

Ayse Naz Erkan, Raia Hadsell, Pierre Sermanet, Jan Ben, Urs Muller, Yann LeCun

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A novel probabilistic online learning framework for autonomous off-road robot navigation is proposed. The system is purely vision-based and is particularly designed for predicting traversability in unknown or rapidly changing environments. It uses self-supervised learning to quickly adapt to novel terrains after processing a small number of frames, and it can recognize terrain elements such as paths, man-made structures, and natural obstacles at ranges up to 30 meters. The system is developed on the LAGR mobile robot platform and the performance is evaluated using multiple metrics, including ground truth.

Original language	English (US)
Title of host publication	Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007
Pages	2421-2426
Number of pages	6
DOIs	https://doi.org/10.1109/IROS.2007.4399622
State	Published - 2007
Event	2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007 - San Diego, CA, United States Duration: Oct 29 2007 → Nov 2 2007

Publication series

Name	IEEE International Conference on Intelligent Robots and Systems

Other

Other	2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007
Country/Territory	United States
City	San Diego, CA
Period	10/29/07 → 11/2/07

ASJC Scopus subject areas

Control and Systems Engineering
Software
Computer Vision and Pattern Recognition
Computer Science Applications

Access to Document

10.1109/IROS.2007.4399622

Cite this

Erkan, A. N., Hadsell, R., Sermanet, P., Ben, J., Muller, U., & LeCun, Y. (2007). Adaptive long range vision in unstructured terrain. In Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007 (pp. 2421-2426). Article 4399622 (IEEE International Conference on Intelligent Robots and Systems). https://doi.org/10.1109/IROS.2007.4399622

Adaptive long range vision in unstructured terrain. / Erkan, Ayse Naz; Hadsell, Raia; Sermanet, Pierre et al.
Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007. 2007. p. 2421-2426 4399622 (IEEE International Conference on Intelligent Robots and Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Erkan, AN, Hadsell, R, Sermanet, P, Ben, J, Muller, U & LeCun, Y 2007, Adaptive long range vision in unstructured terrain. in Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007., 4399622, IEEE International Conference on Intelligent Robots and Systems, pp. 2421-2426, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007, San Diego, CA, United States, 10/29/07. https://doi.org/10.1109/IROS.2007.4399622

@inproceedings{4685c9b6a54f4743b7e122039ab5fe85,

title = "Adaptive long range vision in unstructured terrain",

abstract = "A novel probabilistic online learning framework for autonomous off-road robot navigation is proposed. The system is purely vision-based and is particularly designed for predicting traversability in unknown or rapidly changing environments. It uses self-supervised learning to quickly adapt to novel terrains after processing a small number of frames, and it can recognize terrain elements such as paths, man-made structures, and natural obstacles at ranges up to 30 meters. The system is developed on the LAGR mobile robot platform and the performance is evaluated using multiple metrics, including ground truth.",

author = "Erkan, {Ayse Naz} and Raia Hadsell and Pierre Sermanet and Jan Ben and Urs Muller and Yann LeCun",

year = "2007",

doi = "10.1109/IROS.2007.4399622",

language = "English (US)",

isbn = "1424409128",

series = "IEEE International Conference on Intelligent Robots and Systems",

pages = "2421--2426",

booktitle = "Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007",

note = "2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007 ; Conference date: 29-10-2007 Through 02-11-2007",

}

TY - GEN

T1 - Adaptive long range vision in unstructured terrain

AU - Erkan, Ayse Naz

AU - Hadsell, Raia

AU - Sermanet, Pierre

AU - Ben, Jan

AU - Muller, Urs

AU - LeCun, Yann

PY - 2007

Y1 - 2007

N2 - A novel probabilistic online learning framework for autonomous off-road robot navigation is proposed. The system is purely vision-based and is particularly designed for predicting traversability in unknown or rapidly changing environments. It uses self-supervised learning to quickly adapt to novel terrains after processing a small number of frames, and it can recognize terrain elements such as paths, man-made structures, and natural obstacles at ranges up to 30 meters. The system is developed on the LAGR mobile robot platform and the performance is evaluated using multiple metrics, including ground truth.

AB - A novel probabilistic online learning framework for autonomous off-road robot navigation is proposed. The system is purely vision-based and is particularly designed for predicting traversability in unknown or rapidly changing environments. It uses self-supervised learning to quickly adapt to novel terrains after processing a small number of frames, and it can recognize terrain elements such as paths, man-made structures, and natural obstacles at ranges up to 30 meters. The system is developed on the LAGR mobile robot platform and the performance is evaluated using multiple metrics, including ground truth.

UR - http://www.scopus.com/inward/record.url?scp=51349150693&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=51349150693&partnerID=8YFLogxK

U2 - 10.1109/IROS.2007.4399622

DO - 10.1109/IROS.2007.4399622

M3 - Conference contribution

AN - SCOPUS:51349150693

SN - 1424409128

SN - 9781424409129

T3 - IEEE International Conference on Intelligent Robots and Systems

SP - 2421

EP - 2426

BT - Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007

T2 - 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007

Y2 - 29 October 2007 through 2 November 2007

ER -

Adaptive long range vision in unstructured terrain

Abstract

Publication series

Other

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this