8 research outputs found

    Guidance, Navigation and Control for Autonomous Close-Range-Rendezvous

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    This article presents the Guidance, Navigation and Control system (Gnc-system) developed by GSOCs On Orbit Servicing (OOS)-group. It is used for research on autonomous rendezvous, optical sensors and operational concepts with the European Proximity Operations Simulator 2.0 (EPOS) facility and inside an End-to-End simulation. Its modular design intends to make it capable of deployment in space on a novel on-board computer with less effort. Major design decisions as well as plans for future development are introduced

    UTeM navigation system: pedestrian and traffic sign detection using CNN algorithm

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    Navigation is a common problem for all drivers, especially university visitors. Unfamiliar place making the driver become careless and unaware, which give hazard to pedestrians and driver itself. Thus, this system aims to solve the problems, by developing mobile navigation with safety features by taking UTeM campus as our scope of the study. The system using algorithm using CNN as an algorithm and the architecture used is Tiny-YOLOv2 to detect traffic signs and pedestrians. To begin, the dataset containing Person and Traffic Sign images and their annotations will first need to be acquired. Then, the CNN model will be trained and tested. As a result, our proposed system shows that the mean average precision for both classes can achieve as 90.44%, when it is implemented in a conventional smartphone. This is proof that our system can provide better capability when it is implemented with a smartphone device. Thus, it contributes to being a new mobile navigation system that can provide multiple capabilities, instead of navigation functions. In conclusion, our system was proven to be a valuable solution for the mobile navigation system. In addition, it is implicated to educate the driver community to be a responsible and alert drivers

    10-Year Anniversary of the European Proximity Operations Simulator 2.0 - Looking Back at Test Campaigns, Rendezvous Research and Facility Improvements

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    Completed in 2009, the European Proximity Operations Simulator 2.0 (EPOS 2.0) succeeded EPOS 1.0 at the German Space Operations Center (GSOC). One of the many contributions the old EPOS 1.0 facility made to spaceflight rendezvous is the verification of the Jena-Optronik laser-based sensors used by the Automated Transfer Vehicle. While EPOS 2.0 builds upon its heritage, it is a completely new design aiming at considerably more complex rendezvous scenarios. During the last ten years, GSOC’s On-Orbit-Servicing and Autonomy group, who operates, maintains and evolves EPOS 2.0, has made numerous contributions to the field of uncooperative rendezvous, using EPOS as its primary tool. After general research in optical navigation in the early 2010s, the OOS group took a leading role in the DLR project On-Orbit-Servicing End-to-End Simulation in 2014. EPOS 2.0 served as the hardware in the loop simulator of the rendezvous phase and contributed substantially to the project’s remarkable success. Over the years, E2E has revealed demanding requirements, leading to numerous facility improvements and extensions. In addition to the OOS group’s research work, numerous and diverse open-loop test campaigns for industry and internal (DLR) customers have shaped the capabilities of EPOS 2.0 significantly

    Robotics and AI-Enabled On-Orbit Operations With Future Generation of Small Satellites

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    The low-cost and short-lead time of small satellites has led to their use in science-based missions, earth observation, and interplanetary missions. Today, they are also key instruments in orchestrating technological demonstrations for On-Orbit Operations (O 3 ) such as inspection and spacecraft servicing with planned roles in active debris removal and on-orbit assembly. This paper provides an overview of the robotics and autonomous systems (RASs) technologies that enable robotic O 3 on smallsat platforms. Major RAS topics such as sensing & perception, guidance, navigation & control (GN&C) microgravity mobility and mobile manipulation, and autonomy are discussed from the perspective of relevant past and planned missions

    A Fuzzy Guidance System for Rendezvous and Pursuit of Moving Targets

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    This article presents the development of a fuzzy guidance system (FGS) for unmanned aerial vehicles capable of pursuing and performing rendezvous with static and mobile targets. The system is designed to allow the vehicle to approach a maneuvering target from a desired direction of arrival and to terminate the rendezvous at a constant distance from the target. In order to perform a rendezvous with a maneuvering target, the desired direction of arrival is adjusted over time to always approach the target from behind, so that the aircraft and target velocity vectors become aligned. The proposed guidance system assumes the presence of an autopilot and uses a set of Takagi–Sugeno fuzzy controllers to generate the orientation and speed references for the velocity and heading control loops, given the relative position and velocity between the aircraft and the target. The FGS treats the target as a mobile waypoint in a 4-D space (position in 2-dimensions, desired crossing heading and speed) and guides the aircraft on suitable trajectories towards the target. Only when the vehicle is close enough to the rendezvous point, the guidance law is complemented with an additional linear controller to manage the terminal formation keeping phase. The capabilities of the proposed rendezvous-FGS are verified in simulation on both maneuvering and non-maneuvering targets. Finally, experimental results using a multi-rotor aerial system are presented for both fixed and accelerating targets

    Advanced LIDAR-based techniques for autonomous navigation of spaceborne and airborne platforms

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    The main goal of this PhD thesis is the development and performance assessment of innovative techniques for the autonomous navigation of aerospace platforms by exploiting data acquired by electro-optical sensors. Specifically, the attention is focused on active LIDAR systems since they globally provide a higher degree of autonomy with respect to passive sensors. Two different areas of research are addressed, namely the autonomous relative navigation of multi-satellite systems and the autonomous navigation of Unmanned Aerial Vehicles. The global aim is to provide solutions able to improve estimation accuracy, computational load, and overall robustness and reliability with respect to the techniques available in the literature. In the space field, missions like on-orbit servicing and active debris removal require a chaser satellite to perform autonomous orbital maneuvers in close-proximity of an uncooperative space target. In this context, a complete pose determination architecture is here proposed, which relies exclusively on three-dimensional measurements (point clouds) provided by a LIDAR system as well as on the knowledge of the target geometry. Customized solutions are envisaged at each step of the pose determination process (acquisition, tracking, refinement) to ensure adequate accuracy level while simultaneously limiting the computational load with respect to other approaches available in the literature. Specific strategies are also foreseen to ensure process robustness by autonomously detecting algorithms' failures. Performance analysis is realized by means of a simulation environment which is conceived to realistically reproduce LIDAR operation, target geometry, and multi-satellite relative dynamics in close-proximity. An innovative method to design trajectories for target monitoring, which are reliable for on-orbit servicing and active debris removal applications since they satisfy both safety and observation requirements, is also presented. On the other hand, the problem of localization and mapping of Unmanned Aerial Vehicles is also tackled since it is of utmost importance to provide autonomous safe navigation capabilities in mission scenarios which foresee flights in complex environments, such as GPS denied or challenging. Specifically, original solutions are proposed for the localization and mapping steps based on the integration of LIDAR and inertial data. Also in this case, particular attention is focused on computational load and robustness issues. Algorithms' performance is evaluated through off-line simulations carried out on the basis of experimental data gathered by means of a purposely conceived setup within an indoor test scenario

    Close Range Tracking of an Uncooperative Target in a Sequence of Photonic Mixer Device (PMD) Images

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    This paper presents a pose estimation routine for tracking attitude and position of an uncooperative tumbling spacecraft during close range rendezvous. The key innovation is the usage of a Photonic Mixer Device (PMD) sensor for the first time during space proximity for tracking the pose of the uncooperative target. This sensor requires lower power consumption and higher resolution if compared with existing flash Light Identification Detection and Ranging (LiDAR) sensors. In addition, the PMD sensor provides two different measurements at the same time: depth information (point cloud) and amplitude of the reflected signal, which generates a grayscale image. In this paper, a hybrid model-based navigation technique that employs both measurements is proposed. The principal pose estimation technique is the iterative closed point algorithm with reverse calibration, which relies on the depth image. The second technique is an image processing pipeline that generates a set of 2D-to-3D feature correspondences between amplitude image and spacecraft model followed by the Efficient Perspective-n-Points (EPnP) algorithm for pose estimation. In this way, we gain a redundant estimation of the target’s current state in real-time without hardware redundancy. The proposed navigation methodology is tested in the German Aerospace Center (DLR)’s European Proximity Operations Simulator. The hybrid navigation technique shows the capability to ensure robust pose estimation of an uncooperative tumbling target under severe illumination conditions. In fact, the EPnP-based technique allows to overcome the limitations of the primary technique when harsh illumination conditions arise
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