Visual-Inertial Estimation and Control for Inspection of a Tumbling Spacecraft: Experimental Results from the International Space Station

O’Connor, Michael D.; Tweddle, Brent; Katz, Jacob G.; Saenz-Otero, Alvar; Miller, David W.; Makowka, Konrad

doi:10.2514/6.2012-4701

Cited by 4 publications

(1 citation statement)

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“…In addition, the effects of disturbance torques acting on the target are modeled as zero-mean Gaussian noises added on the angular acceleration with covariance E{𝜺𝜺 T } = 0.1 2 I 3×3 (N⋅m) 2 . 26 It is initially assumed that the quaternion-expression attitude measurements of the space debris are provided by noncontact measure methods, denoted by {z k }. The measurement errors are also assumed zero-mean Gaussian noises with covariance R k = E{z k z T k } = 0.05 2 I 4×4 .…”

Section: Simulation Studiesmentioning

confidence: 99%

Robust attitude estimation of rotating space debris based on virtual observations of neural network

Zheng

Chen

et al. 2021

Adaptive Control & Signal

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High precise estimation and prediction of the target's attitude motion are key technologies for capturing and removing rotating space debris. In this article, a neural-network-enhanced Kalman filter (NNEKF) is proposed to improve the precision and robustness of attitude estimation algorithm. The main innovation of the NNEKF is to utilize virtual observations of the inertia characteristics to improve the filter's performances. The virtual observations are obtained using a neural network, which is offline trained using simulation data. In order to decrease the number of nodes of the network, the input data are preprocessed using the discrete Fourier transformation method. Moreover, by involving the characteristic frequencies in the input vector, the neural network can extract information from all the past observations, so as to grasp long-term characteristics of the dynamical system. Therefore, the NNEKF can provide more precise estimation of the target's moment of inertia, and furthermore improve the accuracy and robustness of attitude estimation and prediction. Simulation results indicate that the NNEKF can reduce the estimation errors by 39% compared with the conventional EKF method when using the same measurement data. And the accumulation errors of prediction using estimates of the NNEKF is just as 24% as the conventional EKF.

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Section: Simulation Studiesmentioning

confidence: 99%

Robust attitude estimation of rotating space debris based on virtual observations of neural network

Zheng

Chen

et al. 2021

Adaptive Control & Signal

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A review of space robotics technologies for on-orbit servicing

Flores-Abad

Pham

et al. 2014

Progress in Aerospace Sciences

1,049

353

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a b s t r a c tAssessment of spinal stiffness is widely used by manual therapy practitioners as a part of clinical diagnosis and treatment selection. Although studies have commonly found poor reliability of such procedures, conflicting evidence suggests that assessment of spinal stiffness may help predict response to specific treatments. The current study evaluated the criterion validity of manual assessments of spinal stiffness by comparing them to indentation measurements in patients with low back pain (LBP). As part of a standard examination, an experienced clinician assessed passive accessory spinal stiffness of the L3 vertebrae using posterior to anterior (PA) force on the spinous process of L3 in 50 subjects (54% female, mean (SD) age ¼ 33.0 (12.8) years, BMI ¼ 27.0 (6.0) kg/m 2 ) with LBP. A criterion measure of spinal stiffness was performed using mechanized indentation by a blinded second examiner. Results indicated that manual assessments were uncorrelated to criterion measures of stiffness (spearman rho ¼ 0.06, p ¼ 0.67). Similarly, sensitivity and specificity estimates of judgments of hypomobility were low (0.20 e0.45) and likelihood ratios were generally not statistically significant. Sensitivity and specificity of judgments of hypermobility were not calculated due to limited prevalence. Additional analysis found that BMI explained 32% of the variance in the criterion measure of stiffness, yet failed to improve the relationship between assessments. Additional studies should investigate whether manual assessment of stiffness relates to other clinical and biomechanical constructs, such as symptom reproduction, angular rotation, quality of motion, or end feel.Published by Elsevier Ltd.

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