• DocumentCode
    2557345
  • Title

    Development of a high efficiency and high reliable glass cleaning robot with a dirt detect sensor

  • Author

    Katsuki, Yoshio ; Ikeda, Takeshi ; Yamamoto, Motoji

  • Author_Institution
    Faculty of Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
  • fYear
    2011
  • fDate
    25-30 Sept. 2011
  • Firstpage
    5133
  • Lastpage
    5138
  • Abstract
    Cleaning of glass windows for buildings is a dangerous work for human. Automatic cleaning for glass windows has been, thus, expected. Authors have developed an autonomous small-sized robot which can be used for glass window´s cleaning even on not fully-flat walls. There are two major ways for the motion control of the autonomous cleaning mobile robot, which are reaction-based control method and model-based control method. Efficiency of the cleaning using the reaction-based method is lower than one using the model-based method. This study aims to develop a high efficiency and high reliable glass cleaning robot. Thus, we adopt the model-based method for the control of the cleaning robot. For the efficient and reliable cleaning, the robot should follow a desired path accurately. However, the trajectory tracking on a window is not so easy because of gravity and other dynamical effects. Moreover, even if the robot follows the desired path exactly, the robot can not assure a complete cleaning of the glass window. Therefore, the paper discusses a trajectory tracking control problem on the glass window, and also proposes a novel dirt detect sensor and a motion control method to guarantee the completeness of glass window cleaning. The validity of those proposed methods is confirmed by experiments using a window cleaning robot which attracts a window by magnetic force.
  • Keywords
    Cleaning; Glass; Mobile robots; Robot sensing systems; Trajectory; Windows;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on
  • Conference_Location
    San Francisco, CA
  • ISSN
    2153-0858
  • Print_ISBN
    978-1-61284-454-1
  • Type

    conf

  • DOI
    10.1109/IROS.2011.6095187
  • Filename
    6095187