• DocumentCode
    3563756
  • Title

    Development of prediction based emergency obstacle avoidance module by using LIDAR for mobile robot

  • Author

    Takahashi, Mikito ; Kobayashi, Kazuyuki ; Watanabe, Kajiro ; Kinoshita, Tetsuo

  • Author_Institution
    Fac. of Sci. & Eng., Hosei Univ., Tokyo, Japan
  • fYear
    2014
  • Firstpage
    561
  • Lastpage
    564
  • Abstract
    In the real world, safe navigation is one of the primary aims of a mobile robot. For this to be effectively achieved, we must take into account both static and moving obstacles, including sidewalk curbs, ambulatory humans, and moving bicycles. To this end, we have developed a new emergency obstacle avoidance module for moving robots that uses Light Detection and Ranging (LIDAR) to detect static and moving obstacles. The module comprises a tilted LIDAR and a high speed embedded microcontroller. Tilting LIDAR enables the detection of lower sidewalk curbs, which is important for enabling safe navigation. The microcontroller is used for the estimation of obstacle motion and to facilitate rapid initiation of emergency obstacle avoidance maneuvers. By employing a fast embedded microcontroller, we can distinguish between lower-height obstacles and slopes, even on uneven surfaces, in real-time.
  • Keywords
    collision avoidance; microcontrollers; mobile robots; optical radar; fast embedded microcontroller; high speed embedded microcontroller; light detection and ranging; mobile robot; moving obstacle detection; obstacle motion estimation; prediction based emergency obstacle avoidance module; sidewalk curbs; static obstacle detection; tilted LIDAR; Collision avoidance; Laser radar; Mobile robots; Navigation; Predictive models; Robot kinematics; LIDAR; collision avoidance system; prediction obstacle;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Soft Computing and Intelligent Systems (SCIS), 2014 Joint 7th International Conference on and Advanced Intelligent Systems (ISIS), 15th International Symposium on
  • Type

    conf

  • DOI
    10.1109/SCIS-ISIS.2014.7044725
  • Filename
    7044725