• DocumentCode
    13540
  • Title

    Comparisons Between Two Visual Navigation Strategies for Kicking to Virtual Target Point of Humanoid Robots

  • Author

    Chih-Lyang Hwang ; Ying-Jer Chou ; Chien-Wu Lan

  • Author_Institution
    Dept. of Electr. Eng., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan
  • Volume
    62
  • Issue
    11
  • fYear
    2013
  • fDate
    Nov. 2013
  • Firstpage
    3050
  • Lastpage
    3063
  • Abstract
    In this paper, the kick of a ball to the virtual target point (VTP) for humanoid robots (HRs) by two visual navigation strategies is compared. The VTP is not necessary to be known all the time but it must be estimated on line. At the beginning, a neural-network-based vision system (NNBVS) is designed by the connection of four visual windows relative to four pitch angles of HR so that the transform between the image plane and the world coordinates is established for the visual navigation. The first strategy is assumed that the VTP is realized all the time. Based on the derived geometric relation, the corresponding design is established to execute the assigned task. As an HR is far away from the gate (e.g., larger than 1.8 m), two columns of the gate are not recognized by the proposed NNBVS. In addition, the occlusion of an HR by other HRs often occurs for the soccer game. Then the VTP is not detected all the time. Therefore, another strategy is developed to deal with these circumstances. The condition for the second strategy is that the VTP is detectable as the distance between HR and gate is smaller than the recognizable distance. Finally, four representative experiments for the two navigation strategies confirm that each strategy possesses its own advantages and disadvantages.
  • Keywords
    computational geometry; humanoid robots; mobile robots; navigation; robot vision; NNBVS; VTP; geometric relation; humanoid robots; image plane; neural-network-based vision system; occlusion; pitch angles; soccer game; virtual target point; visual navigation strategy; visual windows; Artificial neural networks; Image color analysis; Logic gates; Machine vision; Navigation; Visualization; Humanoid robot; machine vision for localization; modeling using multilayer neural network; posture revision; strategy for visual navigation;
  • fLanguage
    English
  • Journal_Title
    Instrumentation and Measurement, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9456
  • Type

    jour

  • DOI
    10.1109/TIM.2013.2270044
  • Filename
    6601705