• DocumentCode
    498945
  • Title

    Reliable person following approach for mobile robot in indoor environment

  • Author

    Hu, Chun-Hua ; Ma, Xu-dong ; Dai, Xian-zhong

  • Author_Institution
    Telecommun. Dept., Jiangsu Teacher Univ. of Technol., Changzhou, China
  • Volume
    3
  • fYear
    2009
  • fDate
    12-15 July 2009
  • Firstpage
    1815
  • Lastpage
    1821
  • Abstract
    The ability to track and follow a specific person is a key prerequisite of service mobile robots in indoor environments. A novel following method is introduced, which uses the sizes changes of torso in image as the following control parameters and the fuzzy PID controller is employed to design the following controller. The sizes of torso in images are obtained with mobile robot vision tracking method which integrates the color features of upper body clothes region matching method with the Unscented Particle Filter (UPF) tracking method. In order to reliably follow a specific person, the parameters of the PID controller are adjusted using PSO (Particle Swarm Optimization). Various experiments are carried out and the results demonstrate the robustness and reliability in person-following.
  • Keywords
    fuzzy control; mobile robots; particle filtering (numerical methods); particle swarm optimisation; robot vision; target tracking; three-term control; fuzzy PID controller; indoor environment; mobile robot vision tracking; particle swarm optimization; reliable person following approach; service mobile robot; unscented particle filter tracking; upper body clothes region matching; Fuzzy control; Indoor environments; Mobile robots; Particle filters; Particle swarm optimization; Particle tracking; Robustness; Size control; Three-term control; Torso; Mobile robot; Person following; Vision tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2009 International Conference on
  • Conference_Location
    Baoding
  • Print_ISBN
    978-1-4244-3702-3
  • Electronic_ISBN
    978-1-4244-3703-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2009.5212354
  • Filename
    5212354