Abstract-In this paper, we investigate the use of overhead high-resolution three-dimensional (3-D) data for enhancing the performances of an Unmanned Ground Vehicle (UGV) in vegetated terrains. Data were collected using an airborne laser and provided prior to the robot mission. Through extensive and exhaustive field testing, we demonstrate the significance of such data in two areas: robot localization and global path planning. Absolute localization is achieved by registering 3-D local ground ladar data with the global 3-D aerial data. The same data is used to compute traversability maps that are used by the path planner. Vegetation is filtered both in the ground data and in the aerial data in order to recover the load bearing surface.
Abstract-In this paper we address the problem of assessing quantitatively the quality of traversability maps computed from data collected by an airborne laser range finder. Such data is used to plan paths for an unmanned ground vehicle (UGV) prior to the execution of long range traverses. Little attention has been devoted to the problem we address in this paper. We use a unique data set of geodetic control points, real robot navigation data, ground LIDAR (LIght Detection And Ranging) data and aerial imagery, collected during a week long demonstration to support our work.
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