V. Enescu, G. De Cubber, K. Cauwerts, S. A. Berrabah, H. Sahli, M. Nuttin


In this paper, we propose a mobile robot architecture for person tracking, consisting of an active stereo vision module (ASVM) and a navigation module (NM). The first tracks the person in stereo images and controls the pan/tilt unit to keep the target in the visual field. Its output, i.e. the 3D position of the person, is fed to the NM, which drives the robot towards the target while avoiding obstacles. As a peculiarity of the system, there is no feedback from the NM or the robot motion controller (RMC) to the ASVM. While this imparts flexibility in combining the ASVM with a wide range of robot platforms, it puts considerable strain on the ASVM. Indeed, besides the changes in the target dynamics, it has to cope with the robot motion during obstacle avoidance. These disturbances are accommodated by generating target location hypotheses in an efficient manner. Robustness against outliers and occlusions is achieved by employing a multi-hypothesis tracking method - the particle filter - based on a color model of the target. Moreover, to deal with illumination changes, the system adaptively updates the color model of the target. The main contributions of this paper lie in (1) devising a stereo, color-based target tracking method using the stereo geometry constraint and (2) integrating it with a robotic agent in a loosely coupled manner.


  1. Arsenio, A. M. and Banks, J. L. (1999). People detection and tracking by a humanoid robot. Technical report, MIT.
  2. Arulampalam, S., Maskell, S., Gordon, N., and Clapp, T. (2002). A tutorial on particle filters for on-line nonlinear/non-Gaussian Bayesian tracking. IEEE Transactions of Signal Processing, 50(2):174-188.
  3. Beardsley, P., Reid, I., Zisserman, A., and Murray, D. (1995). Active visual navigation using non-metric structure. In 5th International Conference on Computer Vision, pages 58-64, Cambridge, MA, USA.
  4. Comaniciu, D., Ramesh, V., and Meer, P. (2003). Kernelbased object tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25:564-577.
  5. Davison, A. and Murray, D. (1998). Mobile robot localization using active vision. In 5th European Conference on Computer Vision, volume 2, pages 809-825, Freiburg, Germany.
  6. Franz, M.-O. and H.-A., M. (2000). Biomimetic robot navigation. Robotics and Autonomous Systems, 30:133- 153.
  7. Ghita, O. and P.-F., W. (2003). Real time 3d estimation using depth from defocus. Vision, MVA (SME), 16(3):1- 6.
  8. Koren, Y. and Borenstein, J. (1991). Potential field methods and their inherent limitations for mobile robot navigation. In IEEE Conference on Robotics and Automation, pages 1398-1404, Sacramento, California.
  9. Kuniyoshi, Y. and Rougeaux, S. (1999). A humanoid vision system for interactive robots. In 1st Asian Symposium on Industrial Automation and Robotics, pages 13-21.
  10. Nummiaro, K., Koller-Meier, E., and Gool, L. V. (2003). An adaptive color-based particle filter. Image and Vision Computing, 21:99-110.
  11. Nuttin, M., Vanhooydonck, D., Demeester, E., Brussel, H. V., Buijsse, K., Desimpelaere, L., Ramon, P., and Verschelden, T. (2003). A robotic assistant for ambient intelligent meeting rooms. In 1st European Symposium on Ambient Intelligence (EUSAI), pages 304-317, Veldhoven, The Netherlands.
  12. Perez, P., Hue, C., Vermaak, J., and Gangnet, M. (2002). Color-based probabilistic tracking. In European Conf. Computer Vision (ECCV), volume 1, pages 661-675.
  13. PĂ©rez, P., Vermaak, J., and Blake, A. (2004). Data fusion for visual tracking with particles. Proc. IEEE, 92:495- 513.
  14. Ping, H., Sahli, H., Colon, E., and Baudoin, Y. (2001). Visual servoing for robot navigation. In 3rd International Conference on Climbing and Walking Robots: Clawar 2001, pages 255-264, Karlsruhe, Germany.
  15. Schlegel, C., Illmann, J., Jaberg, H., Schuster, M., and Worz, R. (2000). Integrating vision based behaviors with an autonomous robot. Videre: Journal of Computer Vision Research, 1(4):32-60.
  16. Strens, M.-J.-A. and Gregory, I.-N. (2003). Tracking in cluttered images. Image Vision and Computing, 21(10):891-911.
  17. Vieville, T. (1997). A few steps towards 3D active vision. Springer, Berlin.
  18. Waarsing, B., Nuttin, M., and Brussel, H. V. (2003). A software framework for control of multi-sensor, multiactuator systems. In International Conference on Advanced Robotics (ICAR), Coimbra, Portugal.
  19. Wilhelm, T., Bohme, H.-J., and Gross, H.-M. (2004). A multi-modal system for tracking and analyzing faces on a mobile robot. Robotics and Autonomous Systems, 48:31-40.

Paper Citation

in Harvard Style

Enescu V., De Cubber G., Cauwerts K., A. Berrabah S., Sahli H. and Nuttin M. (2005). ACTIVE STEREO VISION-BASED MOBILE ROBOT NAVIGATION FOR PERSON TRACKING . In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 972-8865-30-9, pages 32-39. DOI: 10.5220/0001187300320039

in Bibtex Style

author={V. Enescu and G. De Cubber and K. Cauwerts and S. A. Berrabah and H. Sahli and M. Nuttin},
booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},

in EndNote Style

JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
SN - 972-8865-30-9
AU - Enescu V.
AU - De Cubber G.
AU - Cauwerts K.
AU - A. Berrabah S.
AU - Sahli H.
AU - Nuttin M.
PY - 2005
SP - 32
EP - 39
DO - 10.5220/0001187300320039