• DocumentCode
    1757213
  • Title

    Computer-Vision-Based Wheel Sinkage Estimation for Robot Navigation on Lunar Terrain

  • Author

    Hegde, Guruprasad M. ; Cang Ye ; Robinson, Christopher A. ; Stroupe, Ashley ; Tunstel, Edward

  • Author_Institution
    Dept. of Syst. Eng., Univ. of Arkansas at Little Rock, Little Rock, AR, USA
  • Volume
    18
  • Issue
    4
  • fYear
    2013
  • fDate
    Aug. 2013
  • Firstpage
    1346
  • Lastpage
    1356
  • Abstract
    This paper presents a wheel sinkage detection method that may be used in robotic lunar exploration tasks. The method extracts the boundary line between a robot wheel and lunar soil by segmenting the wheel-soil image captured from a video camera that monitors wheel-soil interaction. The detected boundary is projected onto the soil-free image of the robot wheel to determine the parameters of wheel sinkage. The segmentation method is based on a graph theory. It first clusters a wheel-soil image into homogeneous regions called superpixels and constructs a graph on the superpixels. It then partitions the graph into segments by using normalized cuts. Compared with the existing wheel sinkage detection methods, the proposed algorithm is more robust to illumination condition, shadows, and dust (covering the wheel). The method´s efficacy has been validated by experiments under various conditions.
  • Keywords
    mobile robots; planetary rovers; robot vision; space vehicles; boundary line; computer vision based wheel sinkage estimation; graph theory; lunar soil; lunar terrain; normalized cuts; robot navigation; robot wheel; robotic lunar exploration; sinkage detection; soil free image; superpixels; video camera; wheel soil image segmentation; wheel soil interaction; Lunar robotics; normalized cuts; terrain interface angles; wheel sinkage estimation; wheel–soil interaction;
  • fLanguage
    English
  • Journal_Title
    Mechatronics, IEEE/ASME Transactions on
  • Publisher
    ieee
  • ISSN
    1083-4435
  • Type

    jour

  • DOI
    10.1109/TMECH.2013.2264095
  • Filename
    6525403