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International Conference on Intelligent Robotics and Applications

ICIRA 2017: Intelligent Robotics and Applications pp 335–342Cite as

People Tracking in Unknown Environment Based on Particle Filter and Social Force Model

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10464))

Abstract

In this paper, we introduce a novel scheme for tracking moving person based on particle filter and social force model. The tracking process contains two parts: the predict model and the decision model. We adopt the particle filter algorithm to predict the position and velocity of human. According to the result of prediction, we adapt a sophisticated motion model to calculate the value of social force. Finally, we can control the velocity of robot dynamically through the value of social force.

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Acknowledgment

This work is supported by Shanghai University, and we would like to appreciate the senior engineer, Dr. Wanmi Chen for the support of our paper. We also would like to appreciate the equipment and experiment experience supported by Shanghai Robotics Society.

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Authors and Affiliations

  1. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200072, China

    Yang Wang, Wanmi Chen & Yifan Luo

Authors
  1. Yang Wang
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  2. Wanmi Chen
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  3. Yifan Luo
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Corresponding author

Correspondence to Yang Wang .

Editor information

Editors and Affiliations

  1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

    YongAn Huang

  2. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

    Hao Wu

  3. Institute of Industrial Research, University of Portsmouth, Portsmouth, United Kingdom

    Honghai Liu

  4. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

    Zhouping Yin

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Wang, Y., Chen, W., Luo, Y. (2017). People Tracking in Unknown Environment Based on Particle Filter and Social Force Model. In: Huang, Y., Wu, H., Liu, H., Yin, Z. (eds) Intelligent Robotics and Applications. ICIRA 2017. Lecture Notes in Computer Science(), vol 10464. Springer, Cham. https://doi.org/10.1007/978-3-319-65298-6_31

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  • DOI: https://doi.org/10.1007/978-3-319-65298-6_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65297-9

  • Online ISBN: 978-3-319-65298-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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