Online simultaneous localization and mapping with detection and tracking of moving objects: theory and results from a ground vehicle in crowded urban areas

Author

Wang, Chieh-Chih ; Thorpe, Charles ; Thrun, Sebastian

Author_Institution

Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA

Volume

1

fYear

2003

fDate

14-19 Sept. 2003

Firstpage

842

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.

Keywords

Bayes methods; Kalman filters; image motion analysis; object detection; road vehicles; sensors; tracking; Bayesian formula; Navlab11 vehicle; crowded urban areas; detection and tracking of moving objects problem; ground vehicle; probabilistic approach; simultaneous localization and mapping; Bayesian methods; Land vehicles; Layout; Mobile robots; Object detection; Simultaneous localization and mapping; Urban areas; Vehicle detection; Vehicle dynamics; Vehicle safety;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Automation, 2003. Proceedings. ICRA '03. IEEE International Conference on

ISSN

1050-4729

Print_ISBN

0-7803-7736-2

Type

conf

DOI

10.1109/ROBOT.2003.1241698

Filename

1241698