1,721,076 research outputs found
Autonomous relative navigation around uncooperative spacecraft based on a single camera
Get PDFThe interest of the space community toward missions like On-Orbit Servicing of functional satellite to extend their operative life, or Active Debris Removal to reduce the risk of collision among artificial objects in the most crowded orbital belts, is significantly increasing for both economical and safety aspects. These activities present significant technical challenges and, thus, can be enabled only by increasing the level of autonomy and robustness of space systems in terms of guidance, navigation and control functionalities. Clearly this goal requires the design and development of ad-hoc technologies and algorithms. In this framework, this paper presents an original architecture for relative navigation based on a single passive camera able to fully reconstruct the relative state between a chaser spacecraft and a non-cooperative, known target. The proposed architecture is loosely coupled, meaning that pose determination and full relative state estimation are entrusted to separate, but rigidly interconnected processing blocks. Innovative aspects are relevant to both the pose determination algorithms and the filtering scheme. Preliminary performance assessment is carried out by means of numerical simulations considering multiple realistic target/chaser relative dynamics and target geometries. Results allow demonstrating robustness against measurement error sources caused possibly by image processing as well as fast rotational dynamic
Pose Estimation for Spacecraft Relative Navigation Using Model-based Algorithms
No full textThis paper presents innovative model-based algorithms developed for pose estimation of uncooperative targets by processing sparse three-dimensional point clouds. This topic is of interest for advanced space applications, e.g., on-orbit servicing and active debris removal, which require a chaser spacecraft to execute autonomous maneuvers in close-proximity of a space target. Both the problems of pose acquisition and tracking are addressed. The former one is carried out by combining the concepts of principal component analysis and template matching to limit computational effort and amount of on-board data storage compared with traditional approaches. The latter is entrusted to a customized implementation of the iterative closest point algorithm adopting multiple model-measurement matching strategies and a refinement step to increase robustness and accelerate algorithm convergence. Also, safe transition from acquisition to tracking is implemented by means of autonomous detection of pose acquisition failures. The performance of the proposed techniques is investigated by means of numerical simulations in which the operation of an active LIDAR system as well as the target-chaser relative dynamics are realistically reproduced. Results demonstrate algorithms' effectiveness over a wide range of pose conditions and dealing with targets of variable size and shape, despite considerable sparseness of the measured datasets
TECHNOLOGIES AND ALGORITHMS FOR AUTONOMOUS POSE DETERMINATION FOR SMALL SATELLITES
No full textThis paper investigates the potential of multiple architectures for spacecraft pose determination relying on active and passive electro-optical sensors suitable for being used on board of small satellites. Clearly, each technological solution has its specific impact on the techniques and algorithms necessary to process the acquired data. The goal of these algorithms is to provide frequent and accurate estimates of the parameters representing the relative position and attitude between two space platforms. This information is required for many space applications, like formation flying and on-orbit servicing, which involve the autonomous execution of coordinated manoeuvres between two or more spacecraft flying in close-proximity. The algorithms analysed in this paper have been conceived by the Aerospace Systems Team of the University of Naples “Federico II” to tackle the tasks of pose acquisition and tracking by processing either monocular images, acquired by passive cameras, or three-dimensional point clouds, measured by active (scanning or scanner-less) LIDARs. Numerical simulations and experimental tests (within a dedicated facility) are realized to evaluate algorithms’ performance in terms of pose estimation accuracy and computational efficiency
Attitude Motion Characterization of Resident Space Objects via Fusion of Ground-based and Space-based Light Curves
No full textDue to the growing number of fragmentationrelated debris and the launch of mega constellations of satellites, the characterization of Resident Space Objects has been assuming a growing importance in the context of Space Situational Awareness programs to enable accurate orbit propagations and related functionalities such as collision avoidance. Based on the analysis of light curves, photometric characterization can provide useful information concerning the objects’ surface material, shape, and attitude motion. In this context, this paper proposes an attitude motion classifier of unknown space objects using light curves. In particular, the focus is the combination of data from multiple sensors, either ground or space-based, in order to get a more reliable classification than the one arising from a single photometric measurement. Each light curve is classified using a spectral analysis method based on the Lomb-Scargle Periodogram and the Phase Dispersion Minimization approaches. The classifier’s outputs are then fused first at sensor level and then across multiple sensors to derive a unique classification for the observed space object. The performance of the presented architecture is assessed in a numerical environment able to reproduce synthetic light curves accounting for complex object geometries, and a realistic evolution of orbital and rotational dynamics. A correct classification has been produced for all the considered test cases preliminary proving the effectiveness of the proposed approach
Uncooperative pose estimation with a LIDAR-based system
No full textThis paper aims at investigating the performance of a LIDAR-based system for pose determination of uncooperative targets. This problem is relevant to both debris removal and on-orbit servicing missions, and requires the adoption of suitable electro-optical sensors on board a chaser platform, as well as model-based techniques, for target detection and pose estimation. In this paper, a three dimensional approach is pursued in which the point cloud generated by a LIDAR is exploited for pose estimation. Specifically, the condition of close proximity flight to a large debris is considered, in which the relative motion determines a large variation of debris appearance and coverage in the sensors field of view, thus producing challenging conditions for pose estimation. A customized three dimensional Template Matching approach is proposed for fast and reliable pose initial acquisition, while pose tracking is carried out with an Iterative Closest Point algorithm exploiting different measurement-model matching techniques. Specific solutions are envisaged to speed algorithm convergence and limit the size of the point clouds used for pose initial acquisition and tracking to allow autonomous on-board operation. To investigate proposed approach effectiveness and achievable pose accuracy, a numerical simulation environment is developed implementing realistic debris geometry, debris-chaser close-proximity flight, and sensor operation. Results demonstrate algorithm capability of operating with sparse point clouds and large pose variations, while achieving sub-degree and sub-centimeter accuracy in relative attitude and position, respectively
LIDAR-based Autonomous Pose Determination For a Large Space Debris
No full textRecent NASA simulations regarding the debris population in low Earth orbit have demonstrated the need for the active removal of at least five large objects per year to prevent the triggering of the "Kessler syndrome". However, active debris removal missions pose many significant technological challenges, starting from the rendezvous with an uncooperative target, which is not arranged to be approached by a removal system. In this respect, a major task is to develop reliable and robust techniques for the autonomous determination of the target pose. The aim of this paper is to investigate the performance of a LIDAR-based system for pose determination of a known large debris. LIDAR measurements consist of a 3D-point cloud, so the attention is focused on 3D techniques for pose acquisition and tracking. For pose acquisition, an on-line 3D Template Matching technique is introduced specifically thought for on-board autonomous operations. For pose tracking, different variants of the Iterative Closest Point algorithm are investigated. Specifically, two approaches, namely nearest neighbor and normal shooting, are compared to identify the best trade-off between accuracy and computational resources. To this end, a simulator is developed in which realistic debris geometry and motion is implemented, as well as a safe relative trajectory around the debris, and LIDAR operation. Results demonstrate the effectiveness of the proposed techniques for pose acquisition and tracking
Perspectives and sensing concepts for small UAS sense and avoid
No full textThis paper provides an overview and a performance analysis of sensing approaches aimed at providing small Unmanned Aircraft Systems (UAS) flying in the low altitude airspace with sense and avoid capabilities. Limited weight, size and power resources represent significant challenges especially considering non-cooperative architectures and avoidance of flying obstacles. An analysis of conflict detection performance levels achievable exploiting different sensing architectures, i.e., based on (compact) radar, LIDAR, cameras and multi-sensor systems, is carried out by means of numerical simulations in which 2D frontal collision scenarios are reproduced. Also, an experimental campaign is planned, aimed to test sense and avoid technologies and algorithms using flight data collected by a fleet of small fixed-/rotary-wing UAS. First analyses regarding the performance of non-cooperative vision-based detection and tracking algorithms in a small UAV scenario are finally presented
A vision-based approach to uav detection and tracking in cooperative applications
No full textThis paper presents a visual-based approach that allows an Unmanned Aerial Vehicle (UAV) to detect and track a cooperative flying vehicle autonomously using a monocular camera. The algorithms are based on template matching and morphological filtering, thus being able to operate within a wide range of relative distances (i.e., from a few meters up to several tens of meters), while ensuring robustness against variations of illumination conditions, target scale and background. Furthermore, the image processing chain takes full advantage of navigation hints (i.e., relative positioning and own-ship attitude estimates) to improve the computational efficiency and optimize the trade-off between correct detections, false alarms and missed detections. Clearly, the required exchange of information is enabled by the cooperative nature of the formation through a reliable inter-vehicle data-link. Performance assessment is carried out by exploiting flight data collected during an ad hoc experimental campaign. The proposed approach is a key building block of cooperative architectures designed to improve UAV navigation performance either under nominal GNSS coverage or in GNSS-challenging environments
A review of cooperative and uncooperative spacecraft pose determination techniques for close-proximity operations
No full textThe capability of an active spacecraft to accurately estimate its pose with respect to a target orbiting in close-proximity is required by activities like formation flying, on-orbit servicing, active debris removal, and space exploration. According to the specific mission scenario, pose determination involves theoretical and technological challenges related to the search for the most suitable algorithmic solution and sensor architecture. Electro-optical sensors represent the best technological option being compatible with mass and power limitations of micro and small satellites, and their measurements can be processed to estimate all the pose parameters. The degree of complexity of pose determination largely varies depending on the nature of the targets, which may be cooperative or uncooperative (known or unknown) space objects. In this respect, while cooperative pose determination has been successfully demonstrated in orbit, the uncooperative case is still under study. Since the demand for applications for which pose determination capabilities are mandatory is significantly increasing, a literature review of techniques and algorithms developed for cooperative and uncooperative pose determination by processing data from electro-optical sensors is herein presented. Specifically, their main advantages and drawbacks in terms of accuracy, computational complexity, and sensitivity to variability of pose and target geometry are highlighted
ACTIVE VISION-BASED POSE ESTIMATION OF AN UNCOOPERATIVE TARGET
No full textThis paper aims at investigating the performance of a LIDAR-based system for pose determination of a known debris. A customized template matching tech-nique is implemented for pose initial acquisition, while pose tracking is carried out by Iterative Closest Point algorithms based on different matching approach-es. In order to evaluate the achievable accuracy in pose estimation, a numerical simulator is developed implementing realistic debris geometry, target/removal-system relative dynamics, and sensor operation. Results relevant to a large de-bris in Low Earth Orbit show that even relatively sparse point clouds allow the pose to be computed with sub-degree accuracy in attitude and sub-centimeter accuracy in the relative position
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