Uncooperative pose estimation with a LIDAR-based system

Opromolla, Roberto; Fasano, Giancarmine; Rufino, Giancarlo; Grassi, Michele

doi:10.1016/j.actaastro.2014.11.003

Cited by 94 publications

(55 citation statements)

References 26 publications

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“…Having found and matched the pixel coordinates of the five corners on the basis of the distances with respect to the centroid, it is possible to evaluate the rotation matrix and the translation vector with respect to the target, that means the exterior orientation, using the OpenCV solvePnP algorithm that minimizes the reprojection error by using the LevenbergMarquardt method. More in general, for a known target, it could be possible to compute the pose using an approach based on 3D Template-Matching and/or Iterative Closest Point (ICP) algorithm [21].…”

Section: A Depth Sensor Characterizationmentioning

confidence: 99%

RGB-D camera-based quadrotor navigation in GPS-denied and low light environments using known 3D markers

Vetrella

Chai

Fasano

et al. 2015

2015 International Conference on Unmanned Aircraft Systems (ICUAS)

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This paper presents an original approach for autonomous navigation based on RGB-D data and known 3D markers, where the basic concept is to detect and recognize the markers and then to use them for a straightforward pose estimation solution. The developed algorithms can allow a quadrotor to autonomously fly in (cooperative) GPS denied environments and/or when there is no natural or artificial illumination of the scene, by following a predetermined path consisting of successive targets having a well defined shape and/or color. Algorithms for target detection and recognition based on depth data are described which are optimized for real time use, paying particular attention to the on-board computational load. Experimental tests have been carried out by integrating a RGB-Depth sensor (ASUS Xtion Pro Live) on-board a custom-built quadrotor. First results confirm the potential of the proposed approach. The technique can be applied to different types of unmanned aerial vehicles (UAVs), as well as unmanned ground vehicles (UGVs)

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Section: A Depth Sensor Characterizationmentioning

confidence: 99%

RGB-D camera-based quadrotor navigation in GPS-denied and low light environments using known 3D markers

Vetrella

Chai

Fasano

et al. 2015

2015 International Conference on Unmanned Aircraft Systems (ICUAS)

Self Cite

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“…Moreover, it also provides the users with information about ray intersection with other objects in the scene. RT algorithms have been exploited for analysis of several sensors, for example, laser [7], lidar [8,9], radar [10][11][12], and applications, for example, scene rendering and indoor wireless net design [13][14][15]. With specific reference to SAR imaging, it is worth noting that SAR simulators have been typically developed under the assumption of parallel rays [10,11], which is an adequate approximation for standard remote sensing applications.…”

Section: Introductionmentioning

confidence: 99%

Indoor Operations by FMCW Millimeter Wave SAR Onboard Small UAS: A Simulation Approach

2016

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A dedicated system simulator is presented in this paper for indoor operations onboard small Unmanned Aerial Systems (UAS) by a novel millimeter wave radar sensor. The sensor relies on the principle of Synthetic Aperture Radar (SAR) applied to a Frequency Modulated Continuous Wave (FMCW) radar system. Input to the simulator are both design parameters for Synthetic Aperture Radar (SAR), which should be able to cope with the stringent requirements set by indoor operations, and information about platform navigation and observed scene. The scene generation task is described in detail. This is based on models for point target response on either a completely absorbing background or fluctuating background and ray tracing (RT) techniques. Results obtained from scene processing are finally discussed, giving further insights on expected results from high-resolution observation of an assigned control volume by this novel SAR sensor.

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“…They are robust sensors with respect to the illumination conditions and they usually have a better resolution than the one provided by passive sensors [32]. However, it should be noted that both active and passive sensors experience problems in the detection of very reflective materials (e.g.…”

Section: B Target's Pose Measurementmentioning

confidence: 99%

“…Passive sensors may work in the visible range or infrared range and they have lower hardware complexity than active sensors, they are cheaper and their mass and power consumption is lower [32,33]. However, their resolution is usually poorer than the one of active sensors.…”

Section: B Target's Pose Measurementmentioning

confidence: 99%

Guidance, Navigation, and Control for the Eddy Brake Method

Gómez

Walker

2017

Journal of Guidance, Control, and Dynamics

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Existing active debris removal methods that require physical contact with the target have applicability limitations depending on the maximum angular momentum that can be absorbed. Therefore, a de-tumbling phase prior to the capturing phase may be necessary.The aim of this article is to study the guidance, navigation and control subsystem of the 'Eddy Brake', an active contactless de-tumbling method based on the generation of eddy currents. The article first presents this method and the main requirements for the control module as well as the necessary sensors for pose estimation on-board the chaser. Furthermore, the linear and rotational dynamics based on the Magnetic Tensor Theory are explained in order to model the chaser-target interactions. In addition, the set of 3D nonlinear dynamical equations that model the de-tumbling process are formulated including a specific control strategy with possible inaccuracies and delays derived from the on-board sensors and actuators. Moreover, a stability analysis is developed in the vicinity of a stable asymptotic state for a simplified 2D configuration where an analytical approach is viable.

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Uncooperative pose estimation with a LIDAR-based system

Cited by 94 publications

References 26 publications

RGB-D camera-based quadrotor navigation in GPS-denied and low light environments using known 3D markers

RGB-D camera-based quadrotor navigation in GPS-denied and low light environments using known 3D markers

Indoor Operations by FMCW Millimeter Wave SAR Onboard Small UAS: A Simulation Approach

Guidance, Navigation, and Control for the Eddy Brake Method

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