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A Robust Observation, Planning, and Control Pipeline for Autonomous Rendezvous with Tumbling Targets

Accumulating space debris edges the space domain ever closer to cascading Kessler syndrome, a chain reaction of debris generation that could dramatically inhibit the practical use of space. Meanwhile, a growing number of retired satellites, particularly in higher orbits like geostationary orbit, rem...

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Autores principales: Albee, Keenan, Oestreich, Charles, Specht, Caroline, Terán Espinoza, Antonio, Todd, Jessica, Hokaj, Ian, Lampariello, Roberto, Linares, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8484313/
https://www.ncbi.nlm.nih.gov/pubmed/34604314
http://dx.doi.org/10.3389/frobt.2021.641338
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author Albee, Keenan
Oestreich, Charles
Specht, Caroline
Terán Espinoza, Antonio
Todd, Jessica
Hokaj, Ian
Lampariello, Roberto
Linares, Richard
author_facet Albee, Keenan
Oestreich, Charles
Specht, Caroline
Terán Espinoza, Antonio
Todd, Jessica
Hokaj, Ian
Lampariello, Roberto
Linares, Richard
author_sort Albee, Keenan
collection PubMed
description Accumulating space debris edges the space domain ever closer to cascading Kessler syndrome, a chain reaction of debris generation that could dramatically inhibit the practical use of space. Meanwhile, a growing number of retired satellites, particularly in higher orbits like geostationary orbit, remain nearly functional except for minor but critical malfunctions or fuel depletion. Servicing these ailing satellites and cleaning up “high-value” space debris remains a formidable challenge, but active interception of these targets with autonomous repair and deorbit spacecraft is inching closer toward reality as shown through a variety of rendezvous demonstration missions. However, some practical challenges are still unsolved and undemonstrated. Devoid of station-keeping ability, space debris and fuel-depleted satellites often enter uncontrolled tumbles on-orbit. In order to perform on-orbit servicing or active debris removal, docking spacecraft (the “Chaser”) must account for the tumbling motion of these targets (the “Target”), which is oftentimes not known a priori. Accounting for the tumbling dynamics of the Target, the Chaser spacecraft must have an algorithmic approach to identifying the state of the Target’s tumble, then use this information to produce useful motion planning and control. Furthermore, careful consideration of the inherent uncertainty of any maneuvers must be accounted for in order to provide guarantees on system performance. This study proposes the complete pipeline of rendezvous with such a Target, starting from a standoff estimation point to a mating point fixed in the rotating Target’s body frame. A novel visual estimation algorithm is applied using a 3D time-of-flight camera to perform remote standoff estimation of the Target’s rotational state and its principal axes of rotation. A novel motion planning algorithm is employed, making use of offline simulation of potential Target tumble types to produce a look-up table that is parsed on-orbit using the estimation data. This nonlinear programming-based algorithm accounts for known Target geometry and important practical constraints such as field of view requirements, producing a motion plan in the Target’s rotating body frame. Meanwhile, an uncertainty characterization method is demonstrated which propagates uncertainty in the Target’s tumble uncertainty to provide disturbance bounds on the motion plan’s reference trajectory in the inertial frame. Finally, this uncertainty bound is provided to a robust tube model predictive controller, which provides tube-based robustness guarantees on the system’s ability to follow the reference trajectory translationally. The combination and interfaces of these methods are shown, and some of the practical implications of their use on a planned demonstration on NASA’s Astrobee free-flyer are additionally discussed. Simulation results of each of the components individually and in a complete case study example of the full pipeline are presented as the study prepares to move toward demonstration on the International Space Station.
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spelling pubmed-84843132021-10-02 A Robust Observation, Planning, and Control Pipeline for Autonomous Rendezvous with Tumbling Targets Albee, Keenan Oestreich, Charles Specht, Caroline Terán Espinoza, Antonio Todd, Jessica Hokaj, Ian Lampariello, Roberto Linares, Richard Front Robot AI Robotics and AI Accumulating space debris edges the space domain ever closer to cascading Kessler syndrome, a chain reaction of debris generation that could dramatically inhibit the practical use of space. Meanwhile, a growing number of retired satellites, particularly in higher orbits like geostationary orbit, remain nearly functional except for minor but critical malfunctions or fuel depletion. Servicing these ailing satellites and cleaning up “high-value” space debris remains a formidable challenge, but active interception of these targets with autonomous repair and deorbit spacecraft is inching closer toward reality as shown through a variety of rendezvous demonstration missions. However, some practical challenges are still unsolved and undemonstrated. Devoid of station-keeping ability, space debris and fuel-depleted satellites often enter uncontrolled tumbles on-orbit. In order to perform on-orbit servicing or active debris removal, docking spacecraft (the “Chaser”) must account for the tumbling motion of these targets (the “Target”), which is oftentimes not known a priori. Accounting for the tumbling dynamics of the Target, the Chaser spacecraft must have an algorithmic approach to identifying the state of the Target’s tumble, then use this information to produce useful motion planning and control. Furthermore, careful consideration of the inherent uncertainty of any maneuvers must be accounted for in order to provide guarantees on system performance. This study proposes the complete pipeline of rendezvous with such a Target, starting from a standoff estimation point to a mating point fixed in the rotating Target’s body frame. A novel visual estimation algorithm is applied using a 3D time-of-flight camera to perform remote standoff estimation of the Target’s rotational state and its principal axes of rotation. A novel motion planning algorithm is employed, making use of offline simulation of potential Target tumble types to produce a look-up table that is parsed on-orbit using the estimation data. This nonlinear programming-based algorithm accounts for known Target geometry and important practical constraints such as field of view requirements, producing a motion plan in the Target’s rotating body frame. Meanwhile, an uncertainty characterization method is demonstrated which propagates uncertainty in the Target’s tumble uncertainty to provide disturbance bounds on the motion plan’s reference trajectory in the inertial frame. Finally, this uncertainty bound is provided to a robust tube model predictive controller, which provides tube-based robustness guarantees on the system’s ability to follow the reference trajectory translationally. The combination and interfaces of these methods are shown, and some of the practical implications of their use on a planned demonstration on NASA’s Astrobee free-flyer are additionally discussed. Simulation results of each of the components individually and in a complete case study example of the full pipeline are presented as the study prepares to move toward demonstration on the International Space Station. Frontiers Media S.A. 2021-09-17 /pmc/articles/PMC8484313/ /pubmed/34604314 http://dx.doi.org/10.3389/frobt.2021.641338 Text en Copyright © 2021 Albee, Oestreich, Specht, Terán Espinoza, Todd, Hokaj, Lampariello and Linares. 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
Albee, Keenan
Oestreich, Charles
Specht, Caroline
Terán Espinoza, Antonio
Todd, Jessica
Hokaj, Ian
Lampariello, Roberto
Linares, Richard
A Robust Observation, Planning, and Control Pipeline for Autonomous Rendezvous with Tumbling Targets
title A Robust Observation, Planning, and Control Pipeline for Autonomous Rendezvous with Tumbling Targets
title_full A Robust Observation, Planning, and Control Pipeline for Autonomous Rendezvous with Tumbling Targets
title_fullStr A Robust Observation, Planning, and Control Pipeline for Autonomous Rendezvous with Tumbling Targets
title_full_unstemmed A Robust Observation, Planning, and Control Pipeline for Autonomous Rendezvous with Tumbling Targets
title_short A Robust Observation, Planning, and Control Pipeline for Autonomous Rendezvous with Tumbling Targets
title_sort robust observation, planning, and control pipeline for autonomous rendezvous with tumbling targets
topic Robotics and AI
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8484313/
https://www.ncbi.nlm.nih.gov/pubmed/34604314
http://dx.doi.org/10.3389/frobt.2021.641338
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