Relative Computer Vision-Based Navigation for Small Inspection Spacecraft

Tweddle, Brent; Saenz-Otero, Alvar

doi:10.2514/1.g000687

Cited by 68 publications

(33 citation statements)

References 26 publications

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“…Так, на маке-тах SPHERES для относительной навигации использовались достаточно про-стые круги, два из которых были выделены жирным контуром [18] (рис. 20).…”

Section: рис19 реперные точки и их распознаваниеunclassified

Test-Bench COSMOS for Microsatellite Control System Mock-Ups Modeling and Survey

2016

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Section: рис19 реперные точки и их распознаваниеunclassified

Test-Bench COSMOS for Microsatellite Control System Mock-Ups Modeling and Survey

2016

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“…10) For unmanned missions, the ARD system uses an adjustable light source and three or more reflective element clamps (i.e., retro-reflectors) as point-like features to detect the relative distance and orientation between the chaser and target vehicle based on prior information about reflector locations on the visual marker. [3][4][5][6][7][8] Other ARD systems based on visual detection have been demonstrated for unmanned spacecraft in recent years. [7][8][9] In particular, model-based visual detection algorithms for a single vision sensor or a combined vision/LiDAR sensor have been used successfully to estimate the orientation of a target without a visual marker.…”

Section: A108mentioning

confidence: 99%

“…[3][4][5][6][7][8] Other ARD systems based on visual detection have been demonstrated for unmanned spacecraft in recent years. [7][8][9] In particular, model-based visual detection algorithms for a single vision sensor or a combined vision/LiDAR sensor have been used successfully to estimate the orientation of a target without a visual marker. However, the lack of prior information due to scale variation has reduced estimation accuracy during the final stage of docking.…”

Section: A108mentioning

confidence: 99%

“…Such ARD techniques can be implemented using range, optical, and imaging sensors for longitudinal and lateral guidance. [1][2][3][4][5][6][7][8][9] When these are combined with an onboard navigation system using GPS/INS aids and a star tracker, a spacecraft can automatically maneuver toward a target and perform docking with greater accuracy. 10) For unmanned missions, the ARD system uses an adjustable light source and three or more reflective element clamps (i.e., retro-reflectors) as point-like features to detect the relative distance and orientation between the chaser and target vehicle based on prior information about reflector locations on the visual marker.…”

Section: A108mentioning

confidence: 99%

“…[1][2][3][4][5][6][7][8][9][10] Automatic docking require precise relative pose estimation of the target spacecraft. Many developed space-faring countries have deployed a number of manned and unmanned spacecraft with ARD capability: Progress and Soyuz by RKA in Russia, ATV by ESA in Europe, ETS-VII by NASDA, HTV by JAXA in Japan, the unmanned XSS-11 by the U.S. Air Force, DART by NASA in the USA, Dragon by SpaceX in the USA, and Tiangong 1 and Shenzhou 8 by CNSA in China.…”

Section: A108mentioning

confidence: 99%

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Visual Detection and Servoing for Automated Docking of Unmanned Spacecraft

Cho

Huh

Shim

2014

AEROSPACE TECHNOLOGY JAPAN

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In this paper, we propose a visual servoing algorithm for the automated docking of unmanned spacecraft. The proposed algorithm detects a set of custom visual markers using pyramid-based template matching for scale-invariance, and tracks the set of markers using a particle filter and the continuously adaptive mean-shift (CAMShift) algorithm for nonlinear movement. For fast execution, the proposed algorithm runs on general-purpose graphics processing units (GPGPUs) using compute unified device architecture (CUDA) and multi-platform shared memory parallel programming. The performance of the proposed algorithm is validated in flight tests using an indoor unmanned aerial vehicle (UAV) and a simulated docking adapters which showed satisfactory results.

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An introductory review of swarm technology for spacecraft on‐orbit servicing

Asri,

Zhu

2024

Int Journal of Mech Sys Dyn

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This review paper presents a comprehensive evaluation and forward‐looking perspective on the underexplored topic of servicing target objects using spacecraft swarms. Such targets can be known or unknown, cooperative or uncooperative, and pose significant challenges in modern space operations due to their inherent complexity and unpredictability. Successfully servicing space objects is vital for active debris removal and broader on‐orbit servicing tasks such as satellite maintenance, repair, refueling, orbital assembly, and construction. Significant effort has been invested in the literature to explore the servicing of targets using a single spacecraft. Given its advantages and benefits, this paper expands the discussion to encompass a swarm approach to the problem. This review covers various single‐spacecraft approaches and presents a critical examination of the existing, although limited, body of work dedicated to servicing orbital objects using multiple spacecraft. The focus is also broadened to include some influential studies concerning the characterization, capture, and manipulation of physical objects by general multiagent systems, a subject with significant parallels to the core interest of this manuscript. Furthermore, this article also delves into the realm of simultaneous localization and mapping, highlighting its application within close‐proximity operations in space, especially when dealing with unknown uncooperative targets. Special attention is paid to the benefits that this field can receive from distributed multiagent architectures. Finally, an exploration of the promising field of swarm robotics is presented, with an emphasis on its potential to revolutionize the servicing of orbital target objects. Concurrently, a survey of general research directly engaging swarms in the orbital context is conducted. This review aims to bridge the knowledge gap and stimulate further research in the underexplored domain of servicing space targets with spacecraft swarms.

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Relative Computer Vision-Based Navigation for Small Inspection Spacecraft

Cited by 68 publications

References 26 publications

Test-Bench COSMOS for Microsatellite Control System Mock-Ups Modeling and Survey

Test-Bench COSMOS for Microsatellite Control System Mock-Ups Modeling and Survey

Visual Detection and Servoing for Automated Docking of Unmanned Spacecraft

An introductory review of swarm technology for spacecraft on‐orbit servicing

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