Federated-filter-based unmanned ground vehicle localization using 3D range registration with digital elevation model in outdoor environments

  • Authors:

  • Ji-Hoon Choi;Yong-Woon Park;Jun Kim;Tok-Sun Choe;Jae-Bok Song

  • Affiliations:

  • UGV Technology Directorate, Agency for Defense Development, Yuseong, Daejeon 305-600, Korea;UGV Technology Directorate, Agency for Defense Development, Yuseong, Daejeon 305-600, Korea;UGV Technology Directorate, Agency for Defense Development, Yuseong, Daejeon 305-600, Korea;UGV Technology Directorate, Agency for Defense Development, Yuseong, Daejeon 305-600, Korea;Department of Mechanical Engineering, Korea University, Sungbuk-gu, Seoul 136-713, Korea

  • Venue:
  • Journal of Field Robotics
  • Year:
  • 2012

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Abstract

An integrated GPS/INS does not guarantee localization robustness in outdoor environments, because GPS is vulnerable to external disturbances. However, a digital elevation model (DEM) contains 3D data on the terrain over a specified area and hence can provide in-depth localization information during GPS blockage. This paper proposes federated-filter-based localization using three-dimensional (3D) range registration with a DEM. A no-reset-feedback method is used and a 3D LIDAR sensor, magnetic compass, and odometer are used to correct INS errors in GPS blockage. For 3D range registration with DEM, this paper presents a framework based on the weighted registration scheme of two transformations, pairwise registration and registration with DEM, with the INS position and attitude information. The transformation is first determined by comparing the results of two registration methods with the INS position and is then modified to replace the orientation result of 3D registration with the INS attitude. A multilayered DEM approach using the height of the integrated system is also used to constrain the search range of DEM into three layers near the current unmanned ground vehicle (UGV) position when the corresponding point is searched for in the DEM. Experimental results show that the proposed localization algorithm can greatly enhance the robustness and accuracy of UGV localization in outdoor environments. © 2012 Wiley Periodicals, Inc. © 2012 Wiley Periodicals, Inc.