{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T10:34:11Z","timestamp":1778582051605,"version":"3.51.4"},"reference-count":42,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2017,9,24]],"date-time":"2017-09-24T00:00:00Z","timestamp":1506211200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/s17102197","type":"journal-article","created":{"date-parts":[[2017,9,26]],"date-time":"2017-09-26T04:28:01Z","timestamp":1506400081000},"page":"2197","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Hardware in the Loop Performance Assessment of LIDAR-Based Spacecraft Pose Determination"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4448-7490","authenticated-orcid":false,"given":"Roberto","family":"Opromolla","sequence":"first","affiliation":[{"name":"Department of Industrial Engineering, University of Naples \u201cFederico II\u201d, P.le Tecchio 80, 80125 Naples, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2205-3077","authenticated-orcid":false,"given":"Giancarmine","family":"Fasano","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, University of Naples \u201cFederico II\u201d, P.le Tecchio 80, 80125 Naples, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6353-5219","authenticated-orcid":false,"given":"Giancarlo","family":"Rufino","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, University of Naples \u201cFederico II\u201d, P.le Tecchio 80, 80125 Naples, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michele","family":"Grassi","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, University of Naples \u201cFederico II\u201d, P.le Tecchio 80, 80125 Naples, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,9,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.paerosci.2014.03.002","article-title":"A review of space robotics technologies for on-orbit servicing","volume":"68","author":"Ma","year":"2014","journal-title":"Prog. 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