• DocumentCode
    176413
  • Title

    Optimal site selection for soft landing on asteroid

  • Author

    Jian-geng Li ; Jia Zhen ; Xiao-gang Ruan

  • Author_Institution
    Coll. of Electron. Inf. & Control Eng., Beijing Univ. of Technol., Beijing, China
  • fYear
    2014
  • fDate
    May 31 2014-June 2 2014
  • Firstpage
    2944
  • Lastpage
    2948
  • Abstract
    An algorithm for autonomous selection of optimal landing site based on the image is proposed. Firstly, referenced rocks` shadow and light areas are extracted by the use of double threshold segmentation based on the two-dimensional maximum entropy. Then, the threshold segmentation image is processed further, including the combination of the shadow and light areas in order to form obstacle areas and extracting connected areas etc. However, the selection of the safe landing areas should not only take the safety into consideration, but also pay more attention to the value of scientific research. Therefore, the traditional method should be improved. Finally, the optimal landing site is selected based on fuzzy rules merged expertise. Experiments demonstrate that the algorithm can be used to select the optimal landing site accurately and it proves that the method proposed is feasible and robust.
  • Keywords
    asteroids; astronomical image processing; entry, descent and landing (spacecraft); feature extraction; fuzzy set theory; image segmentation; maximum entropy methods; 2D maximum entropy; asteroid; autonomous optimal landing site selection; fuzzy rules; light area extraction; obstacle area; referenced rock shadow extraction; soft landing; threshold segmentation image processing; Detectors; Entropy; Fitting; Histograms; Image segmentation; Rocks; Safety; Asteroid; Double threshold Segmentation; Fuzzy rules; Obstacles Terrain; Soft landing; Two-dimensional Maximum Entropy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (2014 CCDC), The 26th Chinese
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4799-3707-3
  • Type

    conf

  • DOI
    10.1109/CCDC.2014.6852676
  • Filename
    6852676