Dirk Schulz, Wolfram Burgard, Dieter Fox and Armin B. Cremers

Tracking Multiple Moving Targets with a Mobile Robot using Particle Filters and Statistical Data Association

Proceedings of the IEEE International Conference on Robotics and Automation, 2001

---

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 itis 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 keep track of multiple persons even when the trajectories of two people cross eachother.

---

Bibtex

@InProceedings{Schulz01Track,
   author    = {Schulz, D. and Burgard, W. and Fox,D. and Cremers, A.B.},
   title     = {Tracking Multiple Moving Targetswith a Mobile Robot using Particle Filters and Statistical Data Association}
   booktitle = ICRA,
   year      = 2001
}