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Author: Brent Edward Tweddle
Publisher:
ISBN:
Category :
Languages : en
Pages : 226
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Book Description
The use of computer vision for spacecraft relative navigation and proximity operations within an unknown environment is an enabling technology for a number of future commercial and scientific space missions. This thesis presents three first steps towards a larger research initiative to develop and mature these technologies. The first step that is presented is the design and development of a " flight-traceable" upgrade to the Synchronize Position Hold Engage Reorient Experimental Satellites, known as the SPHERES Goggles. This upgrade enables experimental research and maturation of computer vision based navigation technologies on the SPHERES satellites. The second step that is presented is the development of an algorithm for vision based relative spacecraft navigation that uses a fiducial marker with the minimum number of known point correspondences. An experimental evaluation of this algorithm is presented that determines an upper bound on the accuracy and precision of this system. The third step towards vision based relative navigation in an unknown environment is a preliminary investigation into the computational issues associated with high performance embedded computing. The computational characteristics of vision based relative navigation algorithms are discussed along with the requirements that they impose on computational hardware. A trade study is performed which compares a number of dierent commercially available hardware architectures to determine which would provide the best computational performance per unit of electrical power.
Author: Brent Edward Tweddle
Publisher:
ISBN:
Category :
Languages : en
Pages : 226
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Book Description
The use of computer vision for spacecraft relative navigation and proximity operations within an unknown environment is an enabling technology for a number of future commercial and scientific space missions. This thesis presents three first steps towards a larger research initiative to develop and mature these technologies. The first step that is presented is the design and development of a " flight-traceable" upgrade to the Synchronize Position Hold Engage Reorient Experimental Satellites, known as the SPHERES Goggles. This upgrade enables experimental research and maturation of computer vision based navigation technologies on the SPHERES satellites. The second step that is presented is the development of an algorithm for vision based relative spacecraft navigation that uses a fiducial marker with the minimum number of known point correspondences. An experimental evaluation of this algorithm is presented that determines an upper bound on the accuracy and precision of this system. The third step towards vision based relative navigation in an unknown environment is a preliminary investigation into the computational issues associated with high performance embedded computing. The computational characteristics of vision based relative navigation algorithms are discussed along with the requirements that they impose on computational hardware. A trade study is performed which compares a number of dierent commercially available hardware architectures to determine which would provide the best computational performance per unit of electrical power.
Author: Melanie Katherine Stich
Publisher:
ISBN: 9781339260952
Category :
Languages : en
Pages :
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Book Description
A computer vision-based navigation feasibility study consisting of two navigation algorithms is presented to determine whether computer vision can be used to safely navigate a small semi-autonomous inspection satellite in proximity to the International Space Station. Using stereoscopic image-sensors and computer vision, the relative attitude determination and the relative distance determination algorithms estimate the inspection satellite's relative position in relation to its host spacecraft. An algorithm needed to calibrate the stereo camera system is presented, and this calibration method is discussed. These relative navigation algorithms are tested in NASA Johnson Space Center's simulation software, Engineering Dynamic On-board Ubiquitous Graphics (DOUG) Graphics for Exploration (EDGE), using a rendered model of the International Space Station to serve as the host spacecraft. Both vision-based algorithms proved to attain successful results, and the recommended future work is discussed.
Author: Brent Edward Tweddle
Publisher:
ISBN:
Category :
Languages : en
Pages : 410
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Book Description
Prior studies have estimated that there are over 100 potential target objects near the Geostationary Orbit belt that are spinning at rates of over 20 rotations per minute. For a number of reasons, it may be desirable to operate in close proximity to these objects for the purposes of inspection, docking and repair. Many of them have an unknown geometric appearance, are uncooperative and non-communicative. These types of characteristics are also shared by a number of asteroid rendezvous missions. In order to safely operate in close proximity to an object in space, it is important to know the target object's position and orientation relative to the inspector satellite, as well as to build a three-dimensional geometric map of the object for relative navigation in future stages of the mission. This type of problem can be solved with many of the typical Simultaneous Localization and Mapping (SLAM) algorithms that are found in the literature. However, if the target object is spinning with signicant angular velocity, it is also important to know the linear and angular velocity of the target object as well as its center of mass, principal axes of inertia and its inertia matrix. This information is essential to being able to propagate the state of the target object to a future time, which is a key capability for any type of proximity operations mission. Most of the typical SLAM algorithms cannot easily provide these types of estimates for high-speed spinning objects. This thesis describes a new approach to solving a SLAM problem for unknown and uncooperative objects that are spinning about an arbitrary axis. It is capable of estimating a geometric map of the target object, as well as its position, orientation, linear velocity, angular velocity, center of mass, principal axes and ratios of inertia. This allows the state of the target object to be propagated to a future time step using Newton's Second Law and Euler's Equation of Rotational Motion, and thereby allowing this future state to be used by the planning and control algorithms for the target spacecraft. In order to properly evaluate this new approach, it is necessary to gather experi
Author: Robert T. Effinger
Publisher:
ISBN:
Category :
Languages : en
Pages : 36
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Author: Anthea Comellini
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
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.
Author:
Publisher:
ISBN:
Category : Representative government and representation
Languages : en
Pages :
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Author: Antoine Petit
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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In this thesis, we address the issue of fully localizing a known object through computer vision, using a monocular camera, what is a central problem in robotics. A particular attention is here paid on space robotics applications, with the aims of providing a unified visual localization system for autonomous navigation purposes for space rendezvous and proximity operations. Two main challenges of the problem are tackled: initially detecting the targeted object and then tracking it frame-by-frame, providing the complete pose between the camera and the object, knowing the 3D CAD model of the object. For detection, the pose estimation process is based on the segmentation of the moving object and on an efficient probabilistic edge-based matching and alignment procedure of a set of synthetic views of the object with a sequence of initial images. For the tracking phase, pose estimation is handled through a 3D model-based tracking algorithm, for which we propose three different types of visual features, pertinently representing the object with its edges, its silhouette and with a set of interest points. The reliability of the localization process is evaluated by propagating the uncertainty from the errors of the visual features. This uncertainty besides feeds a linear Kalman filter on the camera velocity parameters. Qualitative and quantitative experiments have been performed on various synthetic and real data, with challenging imaging conditions, showing the efficiency and the benefits of the different contributions, and their compliance with space rendezvous applications.
Author: Connor Robert Beierle
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
This dissertation addresses the development of new hardware-in-the-loop testbeds for spaceborne vision-based navigation. The miniaturization of satellites and trend towards distributed space systems place demanding requirements on the navigation capabilities. In particular, next generation miniature space systems requires high levels of autonomy using limited onboard resources. In this context, vision-based sensors play an important role in providing a robust and passive mean to perform both inertial navigation and relative navigation with respect to space resident objects. The characteristic low-cost, low power consumption, small form factor, and high-dynamic range make vision-based sensors the ideal tool to operate in space. Current testbeds used for validation of vision-based sensors and navigation algorithms are affected by a number of limitations such as limited geometric resolution, radiometric dynamics range, or scope in terms of range of operations and functional modes. To overcome these limitations, this research addresses the design, calibration and utilization of two complementary hardware-in-the loop testbeds which make use of a combination of virtual reality and robotics. The virtual reality testbed is a variable-magnification optical stimulator which consists of a pair of actuated lenses that magnify a monitor. High-fidelity, synthetic scenes of the space environment are rendered to the monitor in real-time and closed-loop to stimulate a vision-based sensor test article. This is done using both computer graphics and machine learning techniques. The physical reality consists of a 7 degrees-of-freedom robotic arm, which positions and orients a vision-based sensor with respect to a target object or scene. Custom illumination devices simulate Earth albedo and Sun light to high fidelity to emulate the illumination conditions present in space. After design and calibration, the resulting testbeds are used in conjunction to validate the performance of new navigation algorithms and train neural networks for navigation of the next generation spacecraft.
Author: Joël Bordeneuve-Guibé
Publisher: Springer
ISBN: 3319175181
Category : Technology & Engineering
Languages : en
Pages : 730
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Book Description
The two first CEAS (Council of European Aerospace Societies) Specialist Conferences on Guidance, Navigation and Control (CEAS EuroGNC) were held in Munich, Germany in 2011 and in Delft, The Netherlands in 2013. ONERA The French Aerospace Lab, ISAE (Institut Supérieur de l’Aéronautique et de l’Espace) and ENAC (Ecole Nationale de l’Aviation Civile) accepted the challenge of jointly organizing the 3rd edition. The conference aims at promoting new advances in aerospace GNC theory and technologies for enhancing safety, survivability, efficiency, performance, autonomy and intelligence of aerospace systems. It represents a unique forum for communication and information exchange between specialists in the fields of GNC systems design and operation, including air traffic management. This book contains the forty best papers and gives an interesting snapshot of the latest advances over the following topics: l Control theory, analysis, and design l Novel navigation, estimation, and tracking methods l Aircraft, spacecraft, missile and UAV guidance, navigation, and control l Flight testing and experimental results l Intelligent control in aerospace applications l Aerospace robotics and unmanned/autonomous systems l Sensor systems for guidance, navigation and control l Guidance, navigation, and control concepts in air traffic control systems For the 3rd CEAS Specialist Conference on Guidance, Navigation and Control the International Program Committee conducted a formal review process. Each paper was reviewed in compliance with standard journal practice by at least two independent and anonymous reviewers. The papers published in this book were selected from the conference proceedings based on the results and recommendations from the reviewers.
Author: Francesco Branz
Publisher: Elsevier
ISBN: 0128245425
Category : Technology & Engineering
Languages : en
Pages : 838
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Book Description
Next Generation of CubeSats and SmallSats: Enabling Technologies, Missions, and Markets provides a comprehensive understanding of the small and medium sized satellite approach and its potentialities and limitations. The book analyzes promising applications (e.g., constellations and distributed systems, small science platforms that overachieve relative to their development time and cost) as paradigm-shifting solutions for space exploitation, with an analysis of market statistics and trends and a prediction of where the technologies, and consequently, the field is heading in the next decade. The book also provides a thorough analysis of CubeSat potentialities and applications, and addresses unique technical approaches and systems strategies. Throughout key sections (introduction and background, technology details, systems, applications, and future prospects), the book provides basic design tools scaled to the small satellite problem, assesses the technological state-of-the-art, and describes the most recent advancements with a look to the near future. This new book is for aerospace engineering professionals, advanced students, and designers seeking a broad view of the CubeSat world with a brief historical background, strategies, applications, mission scenarios, new challenges and upcoming advances. Presents a comprehensive and systematic view of the technologies and space missions related to nanosats and smallsats Discusses next generation technologies, up-coming advancements and future perspectives Features the most relevant CubeSat launch initiatives from NASA, ESA, and from developing countries, along with an overview of the New Space CubeSat market
