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This paper presents an experimental activity carried out to evaluate the performance of LIDAR-based algorithms for pose determination of uncooperative space targets. The test setup includes a scanning LIDAR and a monocular camera mounted with a fixed relative geometry, providing 3D (point cloud) and 2D (image) representations of the same scene within the shared portion of their respective Field-of-Views...
This paper presents the performance assessment of innovative model-based algorithms developed for pose estimation of uncooperative targets by processing sparse three-dimensional point clouds. This topic is of interest in the framework of advanced space applications, e.g., on-orbit servicing and active debris removal, which require a chaser spacecraft to execute autonomous relative navigation maneuvers...
This paper presents customized techniques for autonomous localization and mapping of micro Unmanned Aerial Vehicles flying in complex environments, e.g. unexplored, full of obstacles, GPS challenging or denied. The proposed algorithms are aimed at 2D environments and are based on the integration of 3D data, i.e. point clouds acquired by means of a laser scanner (LIDAR), and inertial data given by...
This paper presents an innovative template matching technique to perform the pose acquisition of an uncooperative space target, when no prior information is given about the relative position and attitude parameters. Unlike traditional approaches, the algorithm exploits the principal component analysis to restrain the pose search to a 1 Degree-of-Freedom database built on-line. Hence, both the computational...
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