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The TinyV3RSE Hardware-in-the-Loop Vision-Based Navigation Facility

The increase in number of interplanetary probes has emphasized the need for spacecraft autonomy to reduce overall mission costs and to enable riskier operations without ground support. The perception of the external environment is a critical task for autonomous probes, being fundamental for both mot...

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Autores principales: Panicucci, Paolo, Topputo, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9740262/
https://www.ncbi.nlm.nih.gov/pubmed/36502033
http://dx.doi.org/10.3390/s22239333
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author Panicucci, Paolo
Topputo, Francesco
author_facet Panicucci, Paolo
Topputo, Francesco
author_sort Panicucci, Paolo
collection PubMed
description The increase in number of interplanetary probes has emphasized the need for spacecraft autonomy to reduce overall mission costs and to enable riskier operations without ground support. The perception of the external environment is a critical task for autonomous probes, being fundamental for both motion planning and actuation. Perception is often achieved using navigation sensors which provide measurements of the external environment. For space exploration purposes, cameras are among the sensors that provide navigation information with few constraints at the spacecraft system level. Image processing and vision-based navigation algorithms are exploited to extract information about the external environment and the probe’s position within it from images. It is thus crucial to have the capability to generate realistic image datasets to design, validate, and test autonomous algorithms. This goal is achieved with high-fidelity rendering engines and with hardware-in-the-loop simulations. This work focuses on the latter by presenting a facility developed and used at the Deep-space Astrodynamics Research and Technology (DART) Laboratory at Politecnico di Milano. First, the facility design relationships are established to select hardware components. The critical design parameters of the camera, lens system, and screen are identified and analytical relationships are developed among these parameters. Second, the performances achievable with the chosen components are analytically and numerically studied in terms of geometrical accuracy and optical distortions. Third, the calibration procedures compensating for hardware misalignment and errors are defined. Their performances are evaluated in a laboratory experiment to display the calibration quality. Finally, the facility applicability is demonstrated by testing imageprocessing algorithms for space exploration scenarios.
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spelling pubmed-97402622022-12-11 The TinyV3RSE Hardware-in-the-Loop Vision-Based Navigation Facility Panicucci, Paolo Topputo, Francesco Sensors (Basel) Article The increase in number of interplanetary probes has emphasized the need for spacecraft autonomy to reduce overall mission costs and to enable riskier operations without ground support. The perception of the external environment is a critical task for autonomous probes, being fundamental for both motion planning and actuation. Perception is often achieved using navigation sensors which provide measurements of the external environment. For space exploration purposes, cameras are among the sensors that provide navigation information with few constraints at the spacecraft system level. Image processing and vision-based navigation algorithms are exploited to extract information about the external environment and the probe’s position within it from images. It is thus crucial to have the capability to generate realistic image datasets to design, validate, and test autonomous algorithms. This goal is achieved with high-fidelity rendering engines and with hardware-in-the-loop simulations. This work focuses on the latter by presenting a facility developed and used at the Deep-space Astrodynamics Research and Technology (DART) Laboratory at Politecnico di Milano. First, the facility design relationships are established to select hardware components. The critical design parameters of the camera, lens system, and screen are identified and analytical relationships are developed among these parameters. Second, the performances achievable with the chosen components are analytically and numerically studied in terms of geometrical accuracy and optical distortions. Third, the calibration procedures compensating for hardware misalignment and errors are defined. Their performances are evaluated in a laboratory experiment to display the calibration quality. Finally, the facility applicability is demonstrated by testing imageprocessing algorithms for space exploration scenarios. MDPI 2022-11-30 /pmc/articles/PMC9740262/ /pubmed/36502033 http://dx.doi.org/10.3390/s22239333 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Panicucci, Paolo
Topputo, Francesco
The TinyV3RSE Hardware-in-the-Loop Vision-Based Navigation Facility
title The TinyV3RSE Hardware-in-the-Loop Vision-Based Navigation Facility
title_full The TinyV3RSE Hardware-in-the-Loop Vision-Based Navigation Facility
title_fullStr The TinyV3RSE Hardware-in-the-Loop Vision-Based Navigation Facility
title_full_unstemmed The TinyV3RSE Hardware-in-the-Loop Vision-Based Navigation Facility
title_short The TinyV3RSE Hardware-in-the-Loop Vision-Based Navigation Facility
title_sort tinyv3rse hardware-in-the-loop vision-based navigation facility
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9740262/
https://www.ncbi.nlm.nih.gov/pubmed/36502033
http://dx.doi.org/10.3390/s22239333
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