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

Roberto Opromolla; Giancarmine Fasano; Giancarlo Rufino; Michele Grassi

doi:10.3390/s17102197

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

Sensors (Basel). 2017 Sep 24;17(10):2197. doi: 10.3390/s17102197.

Authors

Roberto Opromolla¹, Giancarmine Fasano², Giancarlo Rufino³, Michele Grassi⁴

Affiliations

¹ Department of Industrial Engineering, University of Naples "Federico II", P.le Tecchio 80, 80125 Naples, Italy. roberto.opromolla@unina.it.
² Department of Industrial Engineering, University of Naples "Federico II", P.le Tecchio 80, 80125 Naples, Italy. giancarmine.fasano@unina.it.
³ Department of Industrial Engineering, University of Naples "Federico II", P.le Tecchio 80, 80125 Naples, Italy. giancarlo.rufino@unina.it.
⁴ Department of Industrial Engineering, University of Naples "Federico II", P.le Tecchio 80, 80125 Naples, Italy. michele.grassi@unina.it.

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.

Keywords: LIDAR; LIDAR/camera relative calibration; hardware-in-the-loop laboratory tests; monocular camera; spacecraft pose determination; uncooperative targets.