Parallel vision-based pose estimation for non-cooperative spacecraft

Li, Ronghua; Zhou, Ying; Chen, Feng; Chen, Yong

doi:10.1177/1687814015594312

Cited by 20 publications

(12 citation statements)

References 14 publications

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“…Stereo images are used in [45] to reconstruct 3-D data, which are then matched with an object model using the iterative closest-point algorithm to estimate pose. Sparse 3-D point clouds recovered with stereo have been employed to estimate pose, for example in [46], where the 3-D points originate from natural keypoints, and [47], which determines image points as the intersections of detected line segments. To achieve more dense reconstruction, Carlo et al [48] suggest the combination of conventional feature-based stereo with shape from shading.…”

Section: B Stereo Approachesmentioning

confidence: 99%

High-Performance Embedded Computing in Space: Evaluation of Platforms for Vision-Based Navigation

Lentaris¹,

Maragos²,

Stratakos³

et al. 2018

Journal of Aerospace Information Systems

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Vision-based navigation has become increasingly important in a variety of space applications for enhancing autonomy and dependability. Future missions, such as active debris removal for remediating the low Earth orbit environment, will rely on novel high-performance avionics to support advanced image processing algorithms with substantial workloads. However, when designing new avionics architectures, constraints relating to the use of electronics in space present great challenges, further exacerbated by the need for significantly faster processing compared to conventional space-grade central processing units. With the long-term goal of designing highperformance embedded computers for space, in this paper, an extended study and tradeoff analysis of a diverse set of computing platforms and architectures (i.e., central processing units, multicore digital signal processors, graphics processing units, and field-programmable gate arrays) are performed with radiation-hardened and commercial offthe-shelf technology. Overall, the study involves more than 30 devices and 10 benchmarks, which are selected after exploring the algorithms and specifications required for vision-based navigation. The present analysis combines literature survey and in-house development/testing to derive a sizable consistent picture of all possible solutions. Among others, the results show that certain 28 nm system-on-chip devices perform faster than space-grade and embedded central processing units by 1-3 orders of magnitude, while consuming less than 10 W. Field-programmable gate array platforms provide the highest performance per watt ratio.

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Section: B Stereo Approachesmentioning

confidence: 99%

High-Performance Embedded Computing in Space: Evaluation of Platforms for Vision-Based Navigation

Lentaris¹,

Maragos²,

Stratakos³

et al. 2018

Journal of Aerospace Information Systems

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“…where J is the Jacobian of the reprojection function f , μ is the damping term, ε is the residual ε X −X , and δ is the sought update to the parameter vector P. Hence, solving Eq. (2) with LM involves iterative solving of the augmented normal equations (11).…”

Section: Pose Estimation From Multi-view Imagesmentioning

confidence: 99%

“…Usually stereovision [8][9][10][11][12][13][14], monocular vision, and lidar (light detection and ranging) [15,16] sensors are used in space applications. Lidar can provide accurate, high-resolution distance measurements but has the drawbacks of substantial mass, power consumption, and cost.…”

Section: Introductionmentioning

confidence: 99%

Rectangular-structure-based pose estimation method for non-cooperative rendezvous

2018

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Pose estimation for spacecraft is widely recognized as an important technology for space applications. Many space missions require accurate relative pose between the chaser and the target spacecraft. Stereovision is a usual mean to estimate the pose of non-cooperative targets during proximity operations. In this paper, an accurate algorithm for pose estimation is proposed by taking advantage of the geometric structure of the object. With stereo cameras, our approach employs the corners of the solar panel as features and uses bundle adjustment to improve the accuracy. Simulation results demonstrate that our method improves the precision and robustness for non-cooperative spacecraft pose estimation. Our laboratory experiments further validate the approach. The results show that the rotation angle error of our method is within 0.8°, and the measurement error in translation is less than 0.4% at the distance from 3 m to 1.2 m.

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“…This is a common method in vision that has been used in many vision applications for pose estimation or for estimation of rotation and translation matrices, which the paper by Li et al [16] has not used. This is the reason that the result in this paper is better than the result by Li et al,…”

Section: Optimization-based Pose Estimation Algorithmmentioning

confidence: 99%

“…Liu et al [15] discuss the effect of the parameters of stereo cameras on the image quality. Li et al [16] extract the intersection of the associated lines as the feature points and use three points to calculate the relative pose between the object coordinates and the world coordinates. Yazdkhasti et al [17] and Fourie et al [18] compute a stereo disparity map by blocking matching algorithms.…”

Section: Introductionmentioning

confidence: 99%

Optimization-based non-cooperative spacecraft pose estimation using stereo cameras during proximity operations

Zhang¹,

Hao²,

Wang³

2017

Appl. Opt.

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Pose estimation for spacecraft is widely recognized as an important technology for space applications. Many space missions require accurate relative pose between the chaser and the target spacecraft. Stereo-vision is a usual mean to estimate the pose of non-cooperative targets during proximity operations. However, the uncertainty of stereovision measurement is still an outstanding issue that needs to be solved. With binocular structure and the geometric structure of the object, we present a robust pose estimation method for non-cooperative spacecraft. Because the solar panel can provide strict geometry constraints, our approach takes the corner points of which as features. After stereo matching, an optimization-based method is proposed to estimate the relative pose between the two spacecraft. Simulation results show that our method improves the precision and robustness of pose estimation. Our system improves the performance with maximum 3D localization error less than 5% and relative rotation angle error less than 1°. Our laboratory experiments further validate the method.

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Parallel vision-based pose estimation for non-cooperative spacecraft

Cited by 20 publications

References 14 publications

High-Performance Embedded Computing in Space: Evaluation of Platforms for Vision-Based Navigation

High-Performance Embedded Computing in Space: Evaluation of Platforms for Vision-Based Navigation

Rectangular-structure-based pose estimation method for non-cooperative rendezvous

Optimization-based non-cooperative spacecraft pose estimation using stereo cameras during proximity operations

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