Pose Measurement Performance of the Argon Relative Navigation Sensor Suite in Simulated-Flight Conditions

Galante, Joseph M.; Eepoel, John Van; Strube, Matt; Gill, Nat; Gonzalez, Marcelo S.; Hyslop, Andrew; Patrick, Bryan

doi:10.2514/6.2012-4927

Cited by 27 publications

(28 citation statements)

References 4 publications

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“…23 However, in the very close range from non-cooperative target, the application of vision system is limited by obscured vision, blurred vision and features loss. 24 For the noncooperative target of nozzle, 2D Laser Range Finder can scan the shape of nozzle for pose measurement. 25 The accuracy of 2D Laser Range Finder is high, but the speed is not fast enough.…”

Section: Introductionmentioning

confidence: 99%

Pose measurement of nozzle based on laser range finders for capturing satellite

Sun

Liu

et al. 2015

Proceedings of the Institution of Mechanical Engineers, Part G:

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Sensors system is considered as one of the most indispensable devices to the mission of capturing a satellite for on-orbit servicing in the space. In this paper, in order to measure the pose of nozzle, six laser range finders are installed in the capturing nozzle device for entering into and capturing nozzle, and a Geometric Axis Approximation (GAA) method is proposed to estimate the pose of satellite nozzle. Six laser range finders are arranged in the configuration of emission radiated at two planes of top and bottom. The pose measurement system is composed of the six laser range finders, applicable for real-time measurement of the ranges from inner surface of nozzle. Based on the properties of nozzle shape and finders arrangement, the GAA method is used to estimate the pose of nozzle by a connecting line between two centers of circles in the top and bottom planes. In the pose estimation of GAA method, solving the nonlinear transcendental equations can be avoided and a simple explicit model is built. Therefore, the GAA method is suitable for real time measurement. In this paper, the theoretical error of GAA method is analyzed, and in the capturing nozzle experiment system, the experiments of pose measurement are carried out. The results of experiments prove the efficiency of GAA method in pose estimation to nozzle based on laser range finders.

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Section: Introductionmentioning

confidence: 99%

Pose measurement of nozzle based on laser range finders for capturing satellite

Sun

Liu

et al. 2015

Proceedings of the Institution of Mechanical Engineers, Part G:

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“…The advantage of 3D LIDAR compared to its 2D counterpart (visual and IR) is operating during day and night, being independent of the target's thermal properties and capable of revealing the underlying structure of an object [17]. Despite current literature offering quite a few LIDAR based relative navigation solutions [7][8][9][10][11][12][13][14][15][16], these present the following deficiencies: First, they rely on the Iterative Closest Point (ICP) [18] method that may settle the estimated rigid body transformation solution in a locally rather than a globally optimum solution. Second, current algorithms require an off-line training process that exploits a 3D model of the expected Target platform.…”

Section: Introductionmentioning

confidence: 99%

H ∞ LIDAR odometry for spacecraft relative navigation

Kechagias‐Stamatis

Aouf

2019

IET Radar, Sonar & Navigation

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Current Light Detection and Ranging (LIDAR) based odometry solutions that are used for spacecraft relative navigation suffer from quite a few deficiencies. These include an off-line training requirement and relying on the Iterative Closest point (ICP) that does not guarantee a globally optimum solution. To encounter this, we suggest a robust architecture that overcomes the problems of current proposals by combining the concepts of 3D local feature matching with an adaptive variant of the H∞ recursive filtering process. Trials on real laser scans of an EnviSat model demonstrate that the proposed architecture affords at least one order of magnitude better accuracy compared to ICP.

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“…Optical-electronic sensors such as laser radar and visionbased system may be more suitable to measure relative position and attitude when the two objects are at the close range, especially in autonomous vehicles or aircrafts [5][6][7]. In addition, the vision-based system based on computer vision is also widely used for object localization in industry manufacturing lines, medical instruments, and some intelligent applications.…”

Section: Introductionmentioning

confidence: 99%

Vision-Based Object Recognition and Precise Localization for Space Body Control

Shangguan¹,

Wang²,

Zhang³

et al. 2019

International Journal of Aerospace Engineering

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The space motion control is an important issue on space robot, rendezvous and docking, small satellite formation, and some on-orbit services. The motion control needs robust object detection and high-precision object localization. Among many sensing systems such as laser radar, inertia sensors, and GPS navigation, vision-based navigation is more adaptive to noncontact applications in the close distance and in high-dynamic environment. In this work, a vision-based system serving for a free-floating robot inside the spacecraft is introduced, and the method to measure space body 6-DOF position-attitude is presented. At first, the deep-learning method is applied for robust object detection in the complex background, and after the object is navigated at the close distance, the reference marker is used for more precise matching and edge detection. After the accurate coordinates are gotten in the image sequence, the object space position and attitude are calculated by the geometry method and used for fine control. The experimental results show that the recognition method based on deep-learning at a distance and marker matching in close range effectively eliminates the false target recognition and improves the precision of positioning at the same time. The testing result shows the recognition accuracy rate is 99.8% and the localization precision is far less than 1% in 1.5 meters. The high-speed camera and embedded electronic platform driven by GPU are applied for accelerating the image processing speed so that the system works at best by 70 frames per second. The contribution of this work is to introduce the deep-learning method for precision motion control and in the meanwhile ensure both the robustness and real time of the system. It aims at making such vision-based system more practicable in the real-space applications.

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Pose Measurement Performance of the Argon Relative Navigation Sensor Suite in Simulated-Flight Conditions

Cited by 27 publications

References 4 publications

Pose measurement of nozzle based on laser range finders for capturing satellite

Pose measurement of nozzle based on laser range finders for capturing satellite

H ∞ LIDAR odometry for spacecraft relative navigation

Vision-Based Object Recognition and Precise Localization for Space Body Control

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