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Sensors 2017, 17(10), 2197; doi:10.3390/s17102197

Hardware in the Loop Performance Assessment of LIDAR-Based Spacecraft Pose Determination

Department of Industrial Engineering, University of Naples “Federico II”, P.le Tecchio 80, 80125 Naples, Italy
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Received: 29 August 2017 / Revised: 15 September 2017 / Accepted: 21 September 2017 / Published: 24 September 2017
(This article belongs to the Section Physical Sensors)
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Abstract

In this paper an original, easy to reproduce, semi-analytic calibration approach is developed for hardware-in-the-loop performance assessment of pose determination algorithms processing point cloud data, collected by imaging a non-cooperative target with LIDARs. The laboratory setup includes a scanning LIDAR, a monocular camera, a scaled-replica of a satellite-like target, and a set of calibration tools. The point clouds are processed by uncooperative model-based algorithms to estimate the target relative position and attitude with respect to the LIDAR. Target images, acquired by a monocular camera operated simultaneously with the LIDAR, are processed applying standard solutions to the Perspective-n-Points problem to get high-accuracy pose estimates which can be used as a benchmark to evaluate the accuracy attained by the LIDAR-based techniques. To this aim, a precise knowledge of the extrinsic relative calibration between the camera and the LIDAR is essential, and it is obtained by implementing an original calibration approach which does not need ad-hoc homologous targets (e.g., retro-reflectors) easily recognizable by the two sensors. The pose determination techniques investigated by this work are of interest to space applications involving close-proximity maneuvers between non-cooperative platforms, e.g., on-orbit servicing and active debris removal. View Full-Text
Keywords: spacecraft pose determination; uncooperative targets; LIDAR; monocular camera; LIDAR/camera relative calibration; hardware-in-the-loop laboratory tests spacecraft pose determination; uncooperative targets; LIDAR; monocular camera; LIDAR/camera relative calibration; hardware-in-the-loop laboratory tests
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Opromolla, R.; Fasano, G.; Rufino, G.; Grassi, M. Hardware in the Loop Performance Assessment of LIDAR-Based Spacecraft Pose Determination. Sensors 2017, 17, 2197.

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