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Online
Simultaneous Localization and Mapping with Detection and Tracking of
Moving Objects: Theory and Results from a Ground
Vehicle in Crowded
Urban Areas
C.-C. Wang, C.
Thorpe and S. Thrun
Abstract |
The
simultaneous localization and mapping (SLAM) with detection and
tracking of
moving objects (DATMO) problem is not only to solve the SLAM problem in
dynamic
environments but also to detect and track these dynamic objects. In
this paper,
we derive the Bayesian formula of the SLAM with DATMO problem, which
provides a
solid basis for understanding and solving this problem. In addition, we
provide
a practical algorithm for performing DATMO from a moving platform
equipped with
range sensors. The probabilistic approach to solve the whole problem
has been
implemented with the Navlab11 vehicle. More than 100 miles of
experiments in
crowded urban areas indicated that SLAM with DATMO is indeed feasible.
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Award |
- Finalist for the Best
Student Paper Award.
- Finalist for
the Wegbreit Best Vision Paper Award.
- Winner
of the 2003 ICRA Best
Conference Paper Award.
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Downlod |
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The full paper is available in PDF.
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Bibtex |
@inproceedings{Wang03a,
author = {Chieh-Chih Wang and Charles Thorpe and
Sebastian Thrun},
title = {Online Simultaneous Localization And
Mapping with Detection And Tracking of Moving Objects: Theory and
Results from a Ground Vehicle in Crowded Urban Areas},
booktitle = {Proceedings of the IEEE International
Conference on Robotics and Automation (ICRA)},
address = {Taipei, Taiwan},
month = {September},
year = {2003},
}
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Copyright ©
Chieh-Chih
(Bob) Wang 1999-2004. All right reserved.
Last Updated: Apr. 23, 2004.
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