• DocumentCode
    713340
  • Title

    Laser scanner based heading angle and distance estimation

  • Author

    Hernandez, Danilo Caceres ; Filonenko, Alexander ; Dongwook Seo ; Kang-Hyun Jo

  • Author_Institution
    Grad. Sch. of Electr. Eng., Univ. of Ulsan, Ulsan, South Korea
  • fYear
    2015
  • fDate
    17-19 March 2015
  • Firstpage
    1718
  • Lastpage
    1722
  • Abstract
    Towards autonomous vehicle navigation the problem of guidance is a major difficulty faced by fully autonomous vehicle. This paper proposes a new method to estimate the heading angle for safe autonomous navigation purpose. The authors focus on unconventional methods of identifying lane markings on a road surface through Laser Measurement System (LMS). This was achieved by taking advantage of the reflection of the laser beam. This method was executed in three steps. Firstly to detect lane markings we employed the Density-based spatial clustering of applications with noise (DBSCAN) method. Secondly, in order to determine the surface course a distance clustering analysis was implemented. Lastly, the steering angle as well as the lateral distance between the heading and the goal point was estimated. Preliminary results were performed and tested on a group of consecutive fames to prove its effectiveness.
  • Keywords
    angular measurement; distance measurement; mobile robots; optical scanners; pattern clustering; road vehicles; DBSCAN; LMS; autonomous vehicle navigation; density-based spatial clustering; distance clustering analysis; distance estimation; guidance problem; heading angle estimation; lane marking detection; lane marking identification; laser beam reflection; laser measurement system; laser scanner; road surface; steering angle; surface course; Laser beams; Measurement by laser beam; Navigation; Roads; Surface emitting lasers; Vehicles; Autonomous vehicle navigation; DBSCAN; Heading angles estimation; Laser beam reflectance; Look-ahead distance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Technology (ICIT), 2015 IEEE International Conference on
  • Conference_Location
    Seville
  • Type

    conf

  • DOI
    10.1109/ICIT.2015.7125345
  • Filename
    7125345