Laser-based Tracking of People and Vehicles by Multiple Mobile Robots

Masafumi Hashimoto, Ryunosuke Izumi, Yuto Tamura, Kazuhiko Takahashi

2014

Abstract

This paper presents laser-based tracking of moving objects conducted by a group of mobile robots located near one another. Each robot finds moving objects such as people, cars, and bicycles in its own laser-scanned images using a binarized occupancy-grid-based method. It then sends laser measurements related to the detected moving objects to a central server. The central server estimates the pose and size of the moving objects via the Kalman filter based on received measurements; it then feeds that information back to the robots. Rule-based and global-nearest-neighbor-based data associations are applied for matching of tracked objects and laser measurements in multitarget environments. In this cooperative tracking method, the central server collects the laser measurements from all robots; hence, the robots can always track invisible or partially invisible objects. The experimental results for two robots in an outdoor environment validate our tracking method.

References

  1. Arra, K. O., and Mozos, O. M., 2010. Special issue on: People Detection and Tracking, In International Journal of Social Robotics, Vol.2, No.1.
  2. Chou, C. T., Li, J. Y., Chang, M. F., and Fu, L. C., 2011. Multi-Robot Cooperation Based Human Tracking System Using Laser Range Finder, In Proceeding of IEEE International Conference on Robotics and Automation (ICRA2011), pp. 532-537.
  3. Fayad, F., and Cherfaoui, V., 2007. Tracking Objects Using a Laser Scanner in Driving Situation based on Modeling Target Shape, In Proceeding of the 2007 IEEE Intelligent Vehicles Symposium (IV2007), pp.44-49.
  4. Hashimoto, M., Ogata, S., Oba, F., and Murayama, T., 2006. A Laser Based Multi-Target Tracking for Mobile Robot, In Intelligent Autonomous Systems 9, pp.135-144.
  5. Kakinuma, K., Hashimoto, M., and Takahashi, K., 2012. Outdoor Pedestrian Tracking by Multiple Mobile Robots Based on SLAM and GPS Fusion, In Proceeding of IEEE/SICE International Symposium on System Integration (SII2012), pp. 422-427.
  6. Konstantinova, P., Udvarev, A., and Semerdjiev, T., 2003. A Study of a Target Tracking Algorithm Using Global Nearest Neighbor Approach, In Proceeding of International Conference on Systems and Technologies.
  7. Mertz, C., Navarro-Serment, L. E., et al., 2013. Moving Object Detection with Laser Scanners, In Journal of Field Robotics, Vol.30, No.1, pp.17-43.
  8. Miyata, T., Ohama, Y., and Ninomiya, Y., 2009. EgoMotion Estimation and Moving Object Tracking using Multi-layer LIDAR, In Proc. of IEEE Intelligent Vehicles Symposium (IV2009), pp.151-156.
  9. Nguyen, V., Martinelli, A., Tomatis, N., and Siegwart, R., 2009. A comparison of Line Extraction Algorithms using 2D Laser Rangefinder for Indoor Mobile Robotics, In Proceeding of 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2009), pp.1929-1934.
  10. Ogawa, T., Sakai, H., Suzuki, Y., Takagi, K., and Morikawa, K., 2011. Pedestrian Detection and Tracking using in-vehicle Lidar for Automotive Application, In Proceeding of IEEE Intelligent Vehicles Symposium (IV2011), pp. 734-739.
  11. Ozaki, M., Kakinuma, K., Hashimoto, M., and Takahashi, K., 2012. Laser-Based Pedestrian Tracking in Outdoor Environments by Multiple Mobile Robots, In Sensors, Vol. 12, pp. 14489-14507.
  12. Sato, S., Hashimoto, M., Takita, M., Takagi, K., and Ogawa, T., 2010. Multilayer Lidar-Based Pedestrian Tracking in Urban Environments, In Proceeding of IEEE Intelligent Vehicles Symposium (IV2010), pp. 849-854.
  13. Sun, Z., Bebis, G., and Miller, R., 2006. On-Road Vehicle Detection: A Review, In IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 28, No. 5, pp. 694-711.
  14. Tsokas, N. A., and Kyriakopoulos, K. J., 2012. MultiRobot Multiple Hypothesis Tracking for Pedestrian Tracking, In Autonomous Robot, Vol. 32, pp. 63-79.
  15. Zhao, H., Sha, J., Zhao, Y., Xi, J., Cui, J., Zha, H., and Shibasaki, R., 2012. Detection and Tracking of Moving Objects at Intersections Using a Network of Laser Scanners, In IEEE Transaction on Intelligent Transportation Systems, Vol.13, No.2, pp.655-670.
Download


Paper Citation


in Harvard Style

Hashimoto M., Izumi R., Tamura Y. and Takahashi K. (2014). Laser-based Tracking of People and Vehicles by Multiple Mobile Robots . In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-040-6, pages 522-527. DOI: 10.5220/0005084205220527


in Bibtex Style

@conference{icinco14,
author={Masafumi Hashimoto and Ryunosuke Izumi and Yuto Tamura and Kazuhiko Takahashi},
title={Laser-based Tracking of People and Vehicles by Multiple Mobile Robots},
booktitle={Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2014},
pages={522-527},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005084205220527},
isbn={978-989-758-040-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - Laser-based Tracking of People and Vehicles by Multiple Mobile Robots
SN - 978-989-758-040-6
AU - Hashimoto M.
AU - Izumi R.
AU - Tamura Y.
AU - Takahashi K.
PY - 2014
SP - 522
EP - 527
DO - 10.5220/0005084205220527