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Tracking multiple moving targets with a mobile robot using particle filters and statistical data association
Abstract
One of the goals in the field of mobile robotics is the development of mobile platforms which operate in populated environments and offer various services to humans. For many tasks it is highly desirable that a robot can determine the positions of the humans in its surrounding. In this paper we present a method for tracking multiple moving objects with a mobile robot. We introduce a sample-based variant of joint probabilistic data association filters to track features originating from individual objects and to solve the correspondence problem between the detected features and the filters. In contrast to standard methods, occlusions are handled explicitly during data association. The technique has been implemented and tested on a real robot. Experiments carried out in a typical office environment show that the method is able to track multiple persons even when the trajectories of two people are crossing each other.
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Cited by
MCMC-based particle filtering for tracking a variable number of interacting targets
Khan, Z., Balch, T., & Dellaert, F. (2005) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2005.223 · Cited by 771
Towards robotic assistants in nursing homes: Challenges and results
Pineau, J., Montemerlo, M., Pollack, M., Roy, N., & Thrun, S. (2003) · Robotics and Autonomous Systems · doi:10.1016/s0921-8890(02)00381-0 · Cited by 640
Simultaneous Localization, Mapping and Moving Object Tracking
Wang, C.-C., Thorpe, C., Thrun, S., Hebert, M., & Durrant-Whyte, H. (2007) · The International Journal of Robotics Research · doi:10.1177/0278364907081229 · Cited by 596
Online Multiperson Tracking-by-Detection from a Single, Uncalibrated Camera
Breitenstein, M. D., Reichlin, F., Leibe, B., Koller-Meier, E., & Van Gool, L. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.232 · Cited by 579
Model based vehicle detection and tracking for autonomous urban driving
Petrovskaya, A., & Thrun, S. (2009) · Autonomous Robots · doi:10.1007/s10514-009-9115-1 · Cited by 430
Metadata
- Authors
- Schulz, D., Burgard, W., Fox, D., & Cremers, A. B.
- Venue
- Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164)
- Publisher
- IEEE
- Published
- 2002-11-13
- Volume
- 2
- Pages
- 1665-1670
- ISSN
- 1050-4729 (ISSN-L)
- OpenAlex
- W2152669093
- Cited by
- 370
- References
- 0
- FWCI
- 25.83
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Schulz, D., Burgard, W., Fox, D., & Cremers, A. B. (2002). Tracking multiple moving targets with a mobile robot using particle filters and statistical data association. Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164). https://doi.org/10.1109/robot.2001.932850
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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