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Autonomous Exploration of Small Bodies Toward Greater Autonomy for Deep Space Missions
Autonomy is becoming increasingly important for the robotic exploration of unpredictable environments. One such example is the approach, proximity operation, and surface exploration of small bodies. In this article, we present an overview of an estimation framework to approach and land on small bodi...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8592236/ https://www.ncbi.nlm.nih.gov/pubmed/34790702 http://dx.doi.org/10.3389/frobt.2021.650885 |
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author | Nesnas, Issa A. D. Hockman, Benjamin J. Bandopadhyay, Saptarshi Morrell, Benjamin J. Lubey, Daniel P. Villa, Jacopo Bayard, David S. Osmundson, Alan Jarvis, Benjamin Bersani, Michele Bhaskaran, Shyam |
author_facet | Nesnas, Issa A. D. Hockman, Benjamin J. Bandopadhyay, Saptarshi Morrell, Benjamin J. Lubey, Daniel P. Villa, Jacopo Bayard, David S. Osmundson, Alan Jarvis, Benjamin Bersani, Michele Bhaskaran, Shyam |
author_sort | Nesnas, Issa A. D. |
collection | PubMed |
description | Autonomy is becoming increasingly important for the robotic exploration of unpredictable environments. One such example is the approach, proximity operation, and surface exploration of small bodies. In this article, we present an overview of an estimation framework to approach and land on small bodies as a key functional capability for an autonomous small-body explorer. We use a multi-phase perception/estimation pipeline with interconnected and overlapping measurements and algorithms to characterize and reach the body, from millions of kilometers down to its surface. We consider a notional spacecraft design that operates across all phases from approach to landing and to maneuvering on the surface of the microgravity body. This SmallSat design makes accommodations to simplify autonomous surface operations. The estimation pipeline combines state-of-the-art techniques with new approaches to estimating the target’s unknown properties across all phases. Centroid and light-curve algorithms estimate the body–spacecraft relative trajectory and rotation, respectively, using a priori knowledge of the initial relative orbit. A new shape-from-silhouette algorithm estimates the pole (i.e., rotation axis) and the initial visual hull that seeds subsequent feature tracking as the body gets more resolved in the narrow field-of-view imager. Feature tracking refines the pole orientation and shape of the body for estimating initial gravity to enable safe close approach. A coarse-shape reconstruction algorithm is used to identify initial landable regions whose hazardous nature would subsequently be assessed by dense 3D reconstruction. Slope stability, thermal, occlusion, and terra-mechanical hazards would be assessed on densely reconstructed regions and continually refined prior to landing. We simulated a mission scenario for approaching a hypothetical small body whose motion and shape were unknown a priori, starting from thousands of kilometers down to 20 km. Results indicate the feasibility of recovering the relative body motion and shape solely relying on onboard measurements and estimates with their associated uncertainties and without human input. Current work continues to mature and characterize the algorithms for the last phases of the estimation framework to land on the surface. |
format | Online Article Text |
id | pubmed-8592236 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85922362021-11-16 Autonomous Exploration of Small Bodies Toward Greater Autonomy for Deep Space Missions Nesnas, Issa A. D. Hockman, Benjamin J. Bandopadhyay, Saptarshi Morrell, Benjamin J. Lubey, Daniel P. Villa, Jacopo Bayard, David S. Osmundson, Alan Jarvis, Benjamin Bersani, Michele Bhaskaran, Shyam Front Robot AI Robotics and AI Autonomy is becoming increasingly important for the robotic exploration of unpredictable environments. One such example is the approach, proximity operation, and surface exploration of small bodies. In this article, we present an overview of an estimation framework to approach and land on small bodies as a key functional capability for an autonomous small-body explorer. We use a multi-phase perception/estimation pipeline with interconnected and overlapping measurements and algorithms to characterize and reach the body, from millions of kilometers down to its surface. We consider a notional spacecraft design that operates across all phases from approach to landing and to maneuvering on the surface of the microgravity body. This SmallSat design makes accommodations to simplify autonomous surface operations. The estimation pipeline combines state-of-the-art techniques with new approaches to estimating the target’s unknown properties across all phases. Centroid and light-curve algorithms estimate the body–spacecraft relative trajectory and rotation, respectively, using a priori knowledge of the initial relative orbit. A new shape-from-silhouette algorithm estimates the pole (i.e., rotation axis) and the initial visual hull that seeds subsequent feature tracking as the body gets more resolved in the narrow field-of-view imager. Feature tracking refines the pole orientation and shape of the body for estimating initial gravity to enable safe close approach. A coarse-shape reconstruction algorithm is used to identify initial landable regions whose hazardous nature would subsequently be assessed by dense 3D reconstruction. Slope stability, thermal, occlusion, and terra-mechanical hazards would be assessed on densely reconstructed regions and continually refined prior to landing. We simulated a mission scenario for approaching a hypothetical small body whose motion and shape were unknown a priori, starting from thousands of kilometers down to 20 km. Results indicate the feasibility of recovering the relative body motion and shape solely relying on onboard measurements and estimates with their associated uncertainties and without human input. Current work continues to mature and characterize the algorithms for the last phases of the estimation framework to land on the surface. Frontiers Media S.A. 2021-11-01 /pmc/articles/PMC8592236/ /pubmed/34790702 http://dx.doi.org/10.3389/frobt.2021.650885 Text en Copyright © 2021 Nesnas, Hockman, Bandopadhyay, Morrell, Lubey, Villa, Bayard, Osmundson, Jarvis, Bersani and Bhaskaran. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Robotics and AI Nesnas, Issa A. D. Hockman, Benjamin J. Bandopadhyay, Saptarshi Morrell, Benjamin J. Lubey, Daniel P. Villa, Jacopo Bayard, David S. Osmundson, Alan Jarvis, Benjamin Bersani, Michele Bhaskaran, Shyam Autonomous Exploration of Small Bodies Toward Greater Autonomy for Deep Space Missions |
title | Autonomous Exploration of Small Bodies Toward Greater Autonomy for Deep Space Missions |
title_full | Autonomous Exploration of Small Bodies Toward Greater Autonomy for Deep Space Missions |
title_fullStr | Autonomous Exploration of Small Bodies Toward Greater Autonomy for Deep Space Missions |
title_full_unstemmed | Autonomous Exploration of Small Bodies Toward Greater Autonomy for Deep Space Missions |
title_short | Autonomous Exploration of Small Bodies Toward Greater Autonomy for Deep Space Missions |
title_sort | autonomous exploration of small bodies toward greater autonomy for deep space missions |
topic | Robotics and AI |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8592236/ https://www.ncbi.nlm.nih.gov/pubmed/34790702 http://dx.doi.org/10.3389/frobt.2021.650885 |
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