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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.

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.
Downlod
The full paper is available in PDF.

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},
}


Copyright © Chieh-Chih (Bob) Wang 1999-2004. All right reserved.
Last Updated: Apr. 23, 2004.