Gait Measurement for Human Behavior Estimation Against Autonomous Mobile Robot

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 302)

Abstract

To realize a safe collision avoidance of autonomous mobile robots, understanding human behavior against the robots is important. This paper has proposed a gait measurement method for human behavior estimation against autonomous mobile robot. The proposed method using a laser range sensor consists of five observed leg patterns recognition and global nearest neighbor (GNN)-based data association with a variable validation region based on the state of each leg. To verify the effectiveness of the proposed system, a verification test in a hospital that staff is recruited as participants were carried out. From the experimental results in the hospital, we confirm that the proposed method can reduce the chance of losing track of both legs and the variable validation region can reduce the chance of false tracking.

Keywords

Autonomous mobile robot Laser range sensor Leg tracking Kalman filter Data association Global nearest neighbor 

Notes

Acknowledgments

This work was supported by Grant-in-Aid for Japan Society for the Promotion of Science (JSPS) Fellows Grant Number 25-5707 and JSPS KAKENHI Grant Number 25709015. We would like to thank the members of Graduate School of Dentistry Osaka University and Research & Development Division of Murata Machinery, LTD. for their help with data collection.

References

  1. 1.
    Evans, J.M.: HelpMate: An Autonomous Mobile Robot Courier for Hospitals, IEEE/RSJ/GI International Conference on Intelligent Robots and Systems, pp. 1695–1700 (1994).Google Scholar
  2. 2.
    Thurun, S., Bennewitz, M., Burgard, W., Cremers, A.B., Dellaert, F., Fox, D., Hähnel, D., Rosenberg, C., Roy, N., Schulte, J., Schulz, D.: MINERVA: A Second-Generation Museum Tour-Guide Robot, IEEE International Conference on Robotics and Automation, pp. 1999–2005 (1999).Google Scholar
  3. 3.
    Lam, C.-P., Chou, C.-T., Chiang, K.-H., Fu, L.-C.: Human-Centered Robot Navigation-Towards a Harmoniously Human-Robot Coexisting Environment, IEEE Transactions on Robotics, Vol. 27, No. 1 (2011).Google Scholar
  4. 4.
    Lu, D.V., Smart, W.D.: Towards More Efficient Navigation for Robots and Humans, IEEE/RSJ International Conference on Intelligent Robots and Systems, (2013).Google Scholar
  5. 5.
    Kakinuma, K., Ozaki, M., Hashimoto, M., Yokoyama, T., Takahashi, K.: Laser-Based Prediction Tracking with Multiple Mobile Robots Using Outdoor SLAM, IEEE International Conference on Robotics and Biomimetics, (2011).Google Scholar
  6. 6.
    Schulz, D., Burgard, W., Fox, D., Cremers, A.B.: People Tracking with Mobile Robot using Sample-based Joint Probabilistic Data Association Filters. International Journal of Robotics Research, pp. 99–115 (2003).Google Scholar
  7. 7.
    Almeida, J., Almeida, A., Araujo, R.: Tracking Multiple Moving Objects for Mobile Robotics Navigation. IEEE International Conference on Emerging Technologies and Factory Automation, pp. 203–210 (2005).Google Scholar
  8. 8.
    Bellotto, N., Hu, H.: Multisensor-Based Human Detection and Tracking for Mobile Service Robots, IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics, Vol. 39, No. 1, pp. 167–181 (2009).CrossRefGoogle Scholar
  9. 9.
    Ratsamee, P., Mae, Y., Ohara, K., Takubo, T., Arai, T.: People Tracking with Body Pose Estimation for Human Path Prediction, IEEE International Conference on Mechatronics and Automation, (2012).Google Scholar
  10. 10.
    Ratsamaee, P., Mae, Y., Ohara, K., Kojima, M., Arai, T.: Social Navigation Model based on Human Intention Analysis using Face Orientation, IEEE/RSJ International Conference on Intelligent Robotics and Systems, (2013).Google Scholar
  11. 11.
    Konstantinova, P., Udvarev, A., Semerdjiev, T.: A Study of a Target Tracking Algorithm Using Global Nearest Neighbor Approach, International Conference on Systems and Technologies, (2003).Google Scholar
  12. 12.
    Bar-Shalom, Y., Willett, P.K., Tian, X.: Tracking and Data Fusion: A Handbook of Algorithms: YBS Publishing, (2011).Google Scholar
  13. 13.
    Yorozu, A., Takahashi, M.: Gait Measurement System for the Elderly Using Laser Range Sensor, International Conference on Control, Mechatronics and Automation, (2013).Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.School of Science for Open and Environmental SystemsKeio UniversityKohoku-kuJapan
  2. 2.Department of System Design EngineeringKeio UniversityKohoku-kuJapan

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