空间失效慢旋卫星视觉特征跟踪与位姿测量

doi:10.7527/S1000-6893.2020.24163

Abstract

Abstract: Space debris or failed satellites often spin around their main inertial axis. Despite their stable state, measurement of their motion state is more difficult than that of a three-axis stable target. Difficulties mainly involve loss of feature points, scale changes and rotation changes in a complex light field environment, and those caused by periodic entry and exit of the target observation surface, as well as increase of cumulative errors and non-convergence of the calculated position and attitude resulted from long-term continuous observation. An optimized target feature database is constructed to turn the matching of the front and back frames in the traditional measurement method into the matching and optimization of the feature points of the current frame and the feature database. In this way, even if an error occurs in the middle process frame, the correct position of the subsequent image frame can still be tracked fairly well. The differential perturbation equation of the pose vector in the Lie algebra space is established to obtain the residual objective function of the measured and estimated values. Based on the maximum posterior probability of the Bayes' rule and the pair-finger transformation rule of Lie group and Lie algebra, the optimal solution of the pose vector is obtained, thereby solving the non-optimizable problem in the Lie group space due to the non-additivity of the pose transformation matrix, and improving the measurement accuracy of the system in the continuous measurement process. Experimental results show that the unoptimized measurement method cannot guarantee effective measurement of the entire rotation cycle, and that increasing the pose optimization process significantly extends the time of continuous stable measurement. For targets with spin motion of 12 (°)/s, the measurement error of the stable segment is within 2°, and that of the rotation angular velocity is 0.12 (°)/s.

Key words: failure satellites, rotating targets, pose estimation, feature tracking, pose optimization

CLC Number:

LIU Zongming, MU Jinzhen, ZHANG Shuo, DU Xuan, CAO Shuqing, ZHANG Yu. Visual feature tracking and pose measurement for slow rotating failure satellites[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(1): 524163-524163.

References

[1] DURRANT W H, BAILEY T. Simultaneous localization and mapping:Part I[J]. IEEE Robotics & Automation Magazine, 2006, 13(2):99-110.
[2] SONNENBURG A, TKOCZ M, JANSCHEK K. Ekf-slam based approach for spacecraft rendezvous navigation with unknown target spacecraft[J]. IFAC Proceedings Volumes, 2010, 43(15):339-344.
[3] AUGENSTEIN S, ROCK S M. Improved frame-to-frame pose tracking during vision only SLAM/SFM with a tumbling target[C]//Proceedings of the IEEE International Conference on Robotics and Automation. Piscataway:IEEE Robotics and Automation Society, 2011:3131-3138.
[4] SCHNITZER F, ANSCHEK K, WILLICH G. Experimental results for image-based geometrical reconstruction for spacecraft rendezvous navigation with unknown and uncooperative target spacecraft[C]//Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems. Piscataway:IEEE Robotics and Automation Society, 2012:5040-5045.
[5] BZY H, ESS A, TUYTELAARS T, et al. Speeded-up robust features[J]. Computer Vision and Image Understanding, 2008, 110:346-359.
[6] TWEDDLE B E. Computer vision-based localization and mapping of an unknown uncooperative and spinning target for spacecraft proximity operations[D]. Cambridge:Massachusetts Institute of Technology, 2013:72-77.
[7] KAESS M, RANGANATHAN A, DELLAERT F. ISAM:Incremental smoothing and mapping[J]. IEEE Transactions on Robotics, 2008, 24(6):1365-1378.
[8] SEGAL S, CARMI A, GURFIL P. Stereovision-based estimation of relative dynamics between non-cooperative satellites:theory and experiments[J]. IEEE Transactions on Control Systems Technology, 2014, 22(2):568-584.
[9] SEGAL S, GURFIL P. Effect of kinematic rotation-translation coupling on relative spacecraft translational dynamics[J]. Journal of Guidance Control & Dynamics, 2009, 32(3):1045-1050.
[10] CONWAY D, MACOMBER B, CAVALIERI K A, et al. Vision-based relative navigation filter for asteroid rendezvous[J]. Advances in the Astronautical Sciences, 2014, 151(1):25-33.
[11] PESCE V, LAVAGNA M, BEVILACQUA R. Stereovision-based pose and inertia estimation of unknown and uncooperative space objects[J]. Advances in Space Research, 2017, 59(1):236-251.
[12] 吴俊君. 移动机器人视觉同时定位与地图构建关键算法研究[D]. 广州:华南理工大学, 2013:22-24. WU J J. Key algorithms of visual simultaneous localization and mapping for mobile robot[D]. Guangzhou:South China University of Technology, 2013:22-24(in Chinese).
[13] RUBLEE E, RABAUD V, KONOLIGE K, et al. ORB:An efficient alternative to sift or surf[C]//Proceedings of the IEEE International Conference on Computer Vision. Barcelona:IEEE Computer Society, 2011:2564-2571.
[14] MICHAEL C, VINCENT L, CHRISTOPH S, et al. Brief:Binary robust independent elementary features[C]//Proceedings of the European Conference on Computer Vision. Heraklion:Springer Verlag, 2010:778-792.
[15] MUR-ARTAL R, MONTIEL J M, TARDOS J D. ORB-SLAM:A versatile and accurate monocular slam system[J]. IEEE Transactions on Robotics, 2015, 31(5):1147-1163.
[16] SCHLEICHER D, BERGASA L M. Real-time hierarchical stereo visual slam in large-scale environments[J]. Robotics and Autonomous Systems, 2010, 58(8):991-1002.
[17] GONG Y, MENG D, SEIBEL E J. Bound constrained bundle adjustment for reliable 3D reconstruction[J]. Optics Express, 2015, 23(8):10771-10786.
[18] GRISETTI G, KUMMERLE R, STACHNISS C, et al. A tutorial on graph-based slam[J]. IEEE Intelligent Transportation Systems Magazine, 2010, 2(4):31-43.
[19] LIU Y, ZHANG H. Indexing visual features:real-time loop closure detection using a tree structure[C]//Proceedings of the IEEE International Conference on Robotics and Automation. Piscataway:IEEE Robotics and Automation Society, 2012:3613-3618.
[20] LUK R, LAM W. Information retrieval:implementing and evaluating search engines[M]. Cambridge:Massachusetts Institute of Technology Press, 2010:120-128.
[21] 高翔, 张涛. 视觉SLAM十四讲从理论到实践[M]. 北京:电子工业出版社, 2017:64-76. GAO X, ZHANG T. Visual slam 14 lectures from theory to practice[M]. Beijing:Electronic Industry Press, 2017:64-76(in Chinese).
[22] 刘宗明, 曹姝清, 张宇, 等. 非合作航天器逆深度参数化姿态估计[J]. 光学精密工程, 2017, 25(2):451-459. LIU Z M, CAO S Q, ZHANG Y, et al. Inverse depth parametrization for attitude estimation of a non-cooperative spacecraft[J]. Optics and Precision Engineering, 2017, 25(2):451-459(in Chinese).

Visual feature tracking and pose measurement for slow rotating failure satellites

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