Littérature scientifique sur le sujet « Non-cooperative rendezvous »

In this paper, the problem of autonomous rendezvous and docking with a non-cooperative target spacecraft is studied. A coupled translational and rotational dynamics of the spacecraft is used, where the rotation matrix is used to represent the attitude of spacecraft to overcome the drawbacks related to the unwinding. An asymptotically stable autonomous rendezvous and docking collision-free controller is proposed based on a novel designed sliding surface. Then, a new nonsingular terminal sliding surface is given, based on which the developed autonomous rendezvous and docking collision-free controller can make the tracking errors converge into a small bounded area near the origin in a finite time. Using artificial potential function and virtual obstacles model established based on cissoid, both controllers ensure the chaser spacecraft strictly remains in the safety area to avoid the collision with the target spacecraft. The effectiveness of the proposed controllers is demonstrated by numerical simulation.

SUMMARYThe technologies of autonomous rendezvous and robotic capturing of non-cooperative targets are very crucial for the future on-orbital service. In this paper, we proposed a method to achieve this aim. Three problems were addressed: the target recognition and pose (position and attitude) measurement based on the stereo vision, the guidance, navigation and control (GNC) of the chaser, and the coordinated plan and control of space robot (CP&C). The pose measurement algorithm includes image filtering, edge detection, line extraction, stereo match and pose computing, et al. Based on the measured values, a certain GNC algorithm was designed for the chaser to approach and rendezvous with the target. Then the CP&C algorithm, which is proved to be advantageous over the traditional separated method, was used to plan and track the trajectories of the base pose and the joint angle. At last, a 3D simulation system was developed to evaluate the proposed method. Simulation results verified the corresponding algorithms.

The robustH∞control for spacecraft rendezvous with a noncooperative target is addressed in this paper. The relative motion of chaser and noncooperative target is firstly modeled as the uncertain system, which contains uncertain orbit parameter and mass. Then theH∞performance and finite time performance are proposed, and a robustH∞controller is developed to drive the chaser to rendezvous with the non-cooperative target in the presence of control input saturation, measurement error, and thrust error. The linear matrix inequality technology is used to derive the sufficient condition of the proposed controller. An illustrative example is finally provided to demonstrate the effectiveness of the controller.

L’objectif de cette thèse est de proposer une solution complète basée sur la vision pour permettre la navigation autonome d’un vaisseau de poursuite (S/C) lors d’opérations de proximité dans l’espace de rendez-vous (RDV) avec une cible non coopérative en utilisant une caméra monoculaire visible.Le rendez-vous autonome est une capacité clé pour répondre aux principaux défis de l’ingénierie spatiale, tels que l’enlèvement actif des débris (ADR) et l’entretien en orbite(OOS). L’ADR vise à éliminer les débris spatiaux, dans les régions protégées en orbite basse, qui sont les plus susceptibles d’entraîner des collisions futures et d’alimenter le syndrome de Kessler, augmentant ainsi le risque pour les engins spatiaux opérationnels.L’OOS comprend des services d’inspection, d’entretien, de réparation, d’assemblage, de ravitaillement et de prolongation de la durée de vie des satellites ou structures en orbite.Lors d’un RDV autonome avec une cible non coopérative, c’est-`a-dire une cible qui n’aide pas / n’interagit pas le chasseur dans les opérations d’acquisition, de poursuite et de rendez-vous, le chasseur doit estimer l’état de la cible `a bord de manière autonome.Les opérations de rendez-vous autonomes nécessitent des mesures précises et actualisées de la pose relative (c’est-à-dire la position et l’attitude de la cible), et la combinaison de capteurs de caméra avec des algorithmes de poursuite peut constituer une solution rentable.La recherche a été divisée en trois études principales : le développement d’un algorithme permettant l’acquisition de la pose initiale (c’est-à-dire la détermination de la pose sans aucune connaissance préalable de cette pose aux instants précédents), le développement d’un algorithme de poursuite récursif (c’est-à-dire d’un algorithme qui exploite les informations sur l’état de la cible à l’instant précédent pour calculer la mise à jour de la pose à l’instant actuel), et le développement d’un filtre de navigation intégrant les mesures provenant de différents capteurs et/ou algorithmes, avec différents taux et délais.En ce qui concerne la phase d’acquisition de la pose, un nouvel algorithme de détection a été développé pour permettre une initialisation rapide de la pose. Une approche est proposée pour récupérer entièrement la pose de la cible en utilisant un ensemble d’invariants et de moments géométriques (c’est-à-dire des caractéristiques globales) calculés à partir des images de la silhouette de la cible. Les caractéristiques globales synthétisent le contenu de l’image dans un vecteur de quelques descripteurs qui changent de valeurs en fonction de la pose relative de la cible. Une base de données des caractéristiques globales est pré-calculée hors ligne en utilisant le modèle géométrique de la cible afin de couvrir tout l’espace de la solution. Au moment de l’exécution, les caractéristiques globales sont calculées sur l’image actuelle acquise et comparées avec la base de données. Différents ensembles de caractéristiques globales ont été comparés afin de sélectionner les plus performants,ce qui a permis d’obtenir un algorithme de détection robuste avec une faible charge de calcul
The aim of this thesis is to propose a full vision-based solution to enable autonomousnavigation of a chaser spacecraft (S/C) during close-proximity operations in space rendezvous(RDV) with a non-cooperative target using a visible monocular camera.Autonomous rendezvous is a key capability to answer main challenges in space engineering,such as Active Debris Removal (ADR) and On-Orbit-Servicing (OOS). ADR aimsat removing the space debris, in low-Earth-orbit protected region, that are more likelyto lead to future collision and feed the Kessler syndrome, thus increasing the risk foroperative spacecrafts. OOS includes inspection, maintenance, repair, assembly, refuelingand life extension services to orbiting S/C or structures. During an autonomous RDVwith a non-cooperative target, i.e., a target that does not assist the chaser in acquisition,tracking and rendezvous operations, the chaser must estimate the target’s state on-boardautonomously. Autonomous RDV operations require accurate, up-to-date measurementsof the relative pose (i.e., position and attitude) of the target, and the combination ofcamera sensors with tracking algorithms can provide a cost effective solution.The research has been divided into three main studies: the development of an algorithmenabling the initial pose acquisition (i.e., the determination of the pose without any priorknowledge of the pose of the target at the previous instants), the development of a recursivetracking algorithm (i.e., an algorithm which exploits the information about thestate of the target at the previous instant to compute the pose update at the currentinstant), and the development of a navigation filter integrating the measurements comingfrom different sensor and/or algorithms, with different rates and delays.For what concerns the pose acquisition phase, a novel detection algorithm has been developedto enable fast pose initialization. An approach is proposed to fully retrieve theobject’s pose using a set of invariants and geometric moments (i.e., global features) computedusing the silhouette images of the target. Global features synthesize the content ofthe image in a vector of few descriptors which change values as a function of the targetrelative pose. A database of global features is pre-computed offline using the target geometricalmodel in order to cover all the solution space. At run-time, global features arecomputed on the current acquired image and compared with the database. Different setsof global features have been compared in order to select the more performing, resultingin a robust detection algorithm having a low computational load.Once an initial estimate of the pose is acquired, a recursive tracking algorithm is initialized.The algorithm relies on the detection and matching of the observed silhouettecontours with the 3D geometric model of the target, which is projected into the imageframe using the estimated pose at the previous instant. Then, the summation of the distances between each projected model points and the matched image points is written as a non-linear function of the unknown pose parameters. The minimization of this costfunction enables the estimation of the pose at the current instant. This algorithm providesfast and very accurate measurements of the relative pose of the target. However,as other recursive trackers, it is prone to divergence. Thus, the detection algorithm isrun in parallel to the tacker in order to provide corrected measurements in case of trackerdivergences. The measurements are then integrated into the chaser navigation filter to provide anoptimal and robust estimate. Vision-based navigation algorithms provide only pose measurements

Thesis (M. S.)--Aerospace Engineering, Georgia Institute of Technology, 2009.
Committee Chair: Panagiotis Tsiotras; Committee Member: Eric Feron; Committee Member: Joseph Saleh; Committee Member: Ryan Russell; Committee Member: William Cook