Vision-based relative state estimation of non-cooperative spacecraft under modeling uncertainty

Segal, Shai; Carmi, Avishy; Gurfil, Pini

doi:10.1109/aero.2011.5747479

Cited by 39 publications

(40 citation statements)

References 13 publications

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“…Rotational Motion can be evaluated independently of the current position and translational movement, as has already exemplarily been shown by Segal in [12]. A simplified model for the target's motion is assumed as a rotational part, rotating the object around it's center of mass s and a translational part, moving the target's center of mass linearly…”

Section: Rotational Motion Estimationmentioning

confidence: 99%

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Pose estimation and trajectory calculation for autonomous close-range rendezvous and docking

Priggemeyer

Dimartino

Roßmann

2015

2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM)

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In order to examine secure ways to perform autonomous satellite servicing applications, this paper provides an approach for close-range motion estimation for rendezvous and docking scenarios. A stereo-camera based method is presented, which generates estimates of the unperturbed motion performed by a completely uncooperative target. No a-priori knowledge about the target has to be provided to accomplish the motion estimation task. A state of the art simulation system is utilized. It provides rigid body dynamics as well as realistic lighting conditions and noise models for the sensor simulation and thus enables the setup of virtual testbeds. Two different satellite models were used to verify the functionality and accuracy of the approach described in this paper. Two KUKA LWRs were used to actuate a model of a Galileo satellite and a stereo-camera rig. This way the method was verified in a physical environment, as well.

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Section: Rotational Motion Estimationmentioning

confidence: 99%

“…The optical observation system is limited to a single rectangular plate of known dimensions. Model-independent approaches were presented in [4], [5] and [12]. Both utilize stereo-camera systems to identify feature points used for a subsequent motion estimation.…”

Section: Introductionmentioning

confidence: 99%

Pose estimation and trajectory calculation for autonomous close-range rendezvous and docking

Priggemeyer

Dimartino

Roßmann

2015

2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM)

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“…Therefore, compared with previous papers (e.g., [12]), this paper offers a complete theoretical and a preliminary experimental development of stereovision-based estimation of the relative state between noncooperative satellites. The uncertainty associated with the target inertia and feature point locations is mitigated based on robust filtering.…”

Section: Introductionmentioning

confidence: 98%

Stereovision-Based Estimation of Relative Dynamics Between Noncooperative Satellites: Theory and Experiments

Segal

Carmi

Gurfil

2014

IEEE Trans. Contr. Syst. Technol.

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149

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Estimating the relative pose and motion of cooperative satellites using on-board sensors is a challenging problem. When the satellites are noncooperative, the problem becomes even more complicated, as there might be poor a priori information about the motion and structure of the target satellite. In this paper, the mentioned problem is solved by using only visual sensors, which measurements are processed through robust filtering algorithms. Using two cameras mounted on a chaser satellite, the relative state with respect to a target satellite, including the position, attitude, and rotational and translational velocities, is estimated. The new approach employs a stereoscopic vision system for tracking a set of feature points on the target spacecraft. The perspective projection of these points on the two cameras constitutes the observation model of an iterated extended Kalman filter (IEKF) estimation scheme. Using new theoretical results, the information contained in the visual data is quantified using the Fisher information matrix. It is shown that, even in the noncooperative case, there is information that can be extracted pertaining to the relative attitude and target structure. Finally, a method is proposed for rendering the relative motion filtering algorithm robust to uncertainties in the target's inertia tensor. This is accomplished by endowing the IEKF with a maximum a posteriori identification scheme for determining the most probable inertia tensor from several available hypotheses. The performance of the new filtering algorithm is validated by Monte-Carlo simulations. Also a preliminary experimental evaluation is provided.

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“…Finally, a Kalman filter was applied as a recursive least squares filter to reduce noise. Oumer and Panin [16] and Segal et al [17] presented a system for feature-based 3D tracking of a noncooperative satellite. Sequential 3D motion estimation from a stereo camera has also been tackled using filtering schemes.…”

Section: Introductionmentioning

confidence: 99%

Relative Attitude Estimation for a Uniform Motion and Slowly Rotating Noncooperative Spacecraft

Zhang

Liu

et al. 2017

Mathematical Problems in Engineering

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This paper presents a novel relative attitude estimation approach for a uniform motion and slowly rotating noncooperative spacecraft. It is assumed that the uniform motion and slowly rotating noncooperative chief spacecraft is in failure or out of control and there is no a priori rotation rate information. We utilize a very fast binary descriptor based on binary robust independent elementary features (BRIEF) to obtain the features of the target, which are rotational invariance and resistance to noise. And then, we propose a novel combination of single candidate random sample consensus (RANSAC) with extended Kalman filter (EKF) that makes use of the available prior probabilistic information from the EKF in the RANSAC model hypothesis stage. The advantage of this combination obviously reduces the sample size to only one, which results in large computational savings without the loss of accuracy. Experimental results from real image sequence of a real model target show that the relative angular error is about 3.5% and the mean angular velocity error is about 0.1 deg/s.

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Vision-based relative state estimation of non-cooperative spacecraft under modeling uncertainty

Cited by 39 publications

References 13 publications

Pose estimation and trajectory calculation for autonomous close-range rendezvous and docking

Pose estimation and trajectory calculation for autonomous close-range rendezvous and docking

Stereovision-Based Estimation of Relative Dynamics Between Noncooperative Satellites: Theory and Experiments

Relative Attitude Estimation for a Uniform Motion and Slowly Rotating Noncooperative Spacecraft

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