Bin WU, Dong YE, Xin ZHANG, et al. Embedded algorithm for relative pose measurement between non-cooperative targets[J]. Optics and precision engineering, 2016, 24(11): 2804-2813.
DOI:
Bin WU, Dong YE, Xin ZHANG, et al. Embedded algorithm for relative pose measurement between non-cooperative targets[J]. Optics and precision engineering, 2016, 24(11): 2804-2813. DOI: 10.3788/OPE.20162411.2804.
Embedded algorithm for relative pose measurement between non-cooperative targets
an algorithm for embedded vision applications was proposed for the relative pose measurement between non-cooperative targets. The edge points were detected by a Canny edge detector and the image thinning was performed in a Field Programming Gate Array(FPGA). Then
elliptic characters on the target were detected by a novel ellipse detection algorithm based on edge contour in a Digital Signal Processor(DSP)
and line features on the target were detected by a real-time and high accuracy method base on Hough Transform(HT). Finally
a ground simulation experiment was performed for a practical mission on orbit. and the relative attitude between target spacecraft and CCD camera was calculated by the obtained ellipse and lines. Experimental results show that the proposed method have been implemented in the embedded system and the update rate is more than 3 Hz. The measurement accuracy becomes poorer with the increasing of measuring distance and that in three directions is different even in the same measure distance. When the measuring distance is less than 4 m
the measurement accuracy in the depth direction is higher than 100 mm
other directions is higher than 60 mm and the angle accuracy is higher than 1°. The obtained results meet the requirement of the embedded system for the system resource
update rate and the detection accuracy.
关键词
Keywords
references
JOEL A, STERGIOS I. A direct least-squares(dls) solution for PnP[C].Proceedings of the IEEE International Conference on Computer Vision, 2011:383-390.
ZHAO R J, ZHANG Q H, ZUO H R, et al.. A method of improving the measuring accuracy of the pose of targets based on outliers-removal[J].Acta Optica Sinica, 2009,29(9):2463-2467.(in Chinese)
VINCENT L, FRANCESC M N, PASCAL F. EPnP:an accurate non-iterative O(n) solution to the PnP problem[J].International J. Computer Vision, 2009, 81(2):155-166.
CUI N G, WANG P,GUO J F,et al.. A review of on-orbit servicing[J].Journal of Astronautics,2007,28(4):805-811.(in Chinese)
MIRAVET C, PASCUAL L, KROUCH E, et al.. An image-based sensor system for autonomous rendez-vous with uncooperative satellites[J].Eprint Arxiv, 2008.
TERUI F, KAMIMURA H, NISHIDA S. Motion estimation to a failed satellite on orbit using stereo vision and 3D model matching[C].9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV'06, 2006:1-8.
CHIEN C H. Target acquisition using natural feature image recognition[C].Aerospace Conference, IEEE,2009:1-7.
XU W F, LIU Y, LIANG B,et al.. Mearsurement of relative poses between two non-cooperative spacecrafts[J].Opt, Precision Eng., 2009, 17(7):1570-1581.(in Chinese)
MIAO X K, ZHU F, DING Q H. Monocular vision pose measurement based on Docking ring component[J]. Acta Optica Sinica, 2013, 33(4):0412006.(in Chinese)
CHAUDHURI D. A simple least squares method for fitting of ellipses and circles depends on border points of a two-tone image and their 3-D extensions[J].Pattern Recognition Letters, 2010, 31(9):818-829.
FITZGIBBON A, PILU M, FISHER R B. Direct least square fitting of ellipses[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1999, 21(5):476-480.
CABRERA J, MEER P. Unbiased estimation of ellipses by bootstrapping[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996, 18(7):752-756.
DUDA R O, HART P E. Pattern Classification and Scene Analysis[M]. New York:Wiley Publishers, 1973.
CHIA A, LEUNG M, ENG H L, et al.. Ellipse detection with Hough transform in one dimensional parametric space[C].Proceedings of IEEE International Conference on Image Processing, 2007, 5:333-336.
CHENG Z G, LIU Y C. Efficient technique for ellipse detection using restricted randomized Hough transform[C].Proceedings of the International Conference on Information Technology, 2004:714-718.
MAI F, HUNG Y, ZHONG H, et al.. A hierarchical approach for fast and robust ellipse extraction[J].Pattern Recognition, 2008, 41(8):2512-2524.
CHIA A S, RAHARDJA S, RAJAN D, et al. A split and merge based ellipse detector with self-correcting capability[J]. IEEE Trans. Image Process, 2011, 20(7):1991-2006.
PRASAD D K, LEUNG M K, CHO S Y. Edge curvature and convexity based ellipse detection method[J]. Pattern Recognition, 201245(9):3204-3221.
LAM L, LEE S W. Thinning methodologies-a comprehensive survey[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992,14(9):869-885.
SHIU Y C, AHMAD S. 3D location of circular and spherical features by monocular model-based vision[C].Proceedings of the IEEE International Conference on Systems, Man and Cybernetics. 1989:576-581.
MCLAUGHLIN R A. Randomized hough transform:improved ellipse detection with comparison[J]. Pattern Recognition Letter, 1998, 19(3):299-305.