• Laser & Optoelectronics Progress
  • Vol. 60, Issue 11, 1106013 (2023)
Liheng Xu1、2、†, Jie Jiang1、2、†,*, and Yan Ma1、2
Author Affiliations
  • 1School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
  • 2Key Laboratory of Precision Opto-Mechatronics Technology, Ministry of Education, Beihang University, Beijing 100191, China
  • show less
    DOI: 10.3788/LOP223406 Cite this Article Set citation alerts
    Liheng Xu, Jie Jiang, Yan Ma. Review of Visual Navigation Technology Based on Craters[J]. Laser & Optoelectronics Progress, 2023, 60(11): 1106013 Copy Citation Text show less
    References

    [1] Yu D Y, Zhang Z, Pan B F et al. Development and trend of artificial intelligent in deep space exploration[J]. Journal of Deep Space Exploration, 7, 11-23(2020).

    [2] Ye P J, Meng L Z, Ma J N et al. Suggestions on artificial intelligence technology application and development in deep space exploration[J]. Journal of Deep Space Exploration, 6, 303-316, 383(2019).

    [3] Ouyang W. Mars autonomous navigation scheme design and analysis[D](2017).

    [4] Zhao S X, Liu Q W, Liu Y Y et al. Navigation-grade resonant fiber-optic gyroscope using ultra-simple white-light multibeam interferometry[J]. Photonics Research, 10, 542-549(2022).

    [5] Campbell T, Furfaro R, Linares R et al. A deep learning approach for optical autonomous planetary relative terrain navigation[EB/OL]. https://experts.arizona.edu/en/publications/a-deep-learning-approach-for-optical-autonomous-planetary-relativ

    [6] Shah Z H, Müller M, Wang T C et al. Deep-learning based denoising and reconstruction of super-resolution structured illumination microscopy images[J]. Photonics Research, 9, B168-B181(2021).

    [7] Wang K K, Xiao L, Yi W et al. Experimental realization of a quantum image classifier via tensor-network-based machine learning[J]. Photonics Research, 9, 2332-2340(2021).

    [8] Ding M, Cao Y F, Wu Q X. Crater detection from gray image of the moon surface[J]. Journal of Applied Sciences, 27, 156-160(2009).

    [9] Zhang C Y, Liang X, Wu F Z et al. Overview of optical navigation for asteroid exploration descent and landing[J]. Infrared and Laser Engineering, 49, 20201009(2020).

    [10] Wright C A, van Eepoel J, Liounis A et al. Relative terrain imaging navigation (Retina) tool for the asteroid redirect robotic mission (Arrm)[EB/OL]. https://ntrs.nasa.gov/citations/20160001876

    [12] Tian Y, Yu M, Yao M B et al. Crater edge-based flexible autonomous navigation for planetary landing[J]. Journal of Navigation, 72, 649-668(2019).

    [13] Johnson A E, Montgomery J F. Overview of terrain relative navigation approaches for precise lunar landing[C](2008).

    [14] Cheng Y, Ansar A. Landmark based position estimation for pinpoint landing on Mars[C], 1573-1578(2006).

    [15] Andersson L E, Whitaker E A[M]. Nasa catalogue of lunar nomenclature(1982).

    [16] J W Ⅲ Head, Fassett C I, Kadish S J et al. Global distribution of large lunar craters: implications for resurfacing and impactor populations[J]. Science, 329, 1504-1507(2010).

    [17] Neumann G A, Zuber M T, Wieczorek M A et al. Lunar impact basins revealed by Gravity Recovery and Interior Laboratory measurements[J]. Science Advances, 1, e1500852(2015).

    [18] Neumann G A, Zuber M T, Wieczorek M A et al. Lunar impact basins revealed by Gravity Recovery and Interior Laboratory measurements[J]. Science Advances, 1, e1500852(2015).

    [19] Povilaitis R Z, Robinson M S, Van Der Bogert C H et al. Crater density differences: exploring regional resurfacing, secondary crater populations, and crater saturation equilibrium on the moon[J]. Planetary and Space Science, 162, 41-51(2018).

    [20] Robbins S J. Hynek, B.M. A global lunar crater database, complete for craters ≥1 KM, Ⅲ: reassessing the lunar crater production function, and lessons learned applied to the global mars crater database[EB/OL]. https://www.hou.usra.edu/meetings/lpsc2018/pdf/2443.pdf

    [21] Salamunićcar G, Lončarić S. GT-57633 catalogue of Martian impact craters developed for evaluation of crater detection algorithms[J]. Planetary and Space Science, 56, 1992-2008(2008).

    [22] Salamunićcar G, Lončarić S, Mazarico E. LU60645GT and MA132843GT catalogues of Lunar and Martian impact craters developed using a crater shape-based interpolation crater detection algorithm for topography data[J]. Planetary and Space Science, 60, 236-247(2012).

    [23] Salamunićcar G, Lončarić S, Pina P et al. MA130301GT catalogue of Martian impact craters and advanced evaluation of crater detection algorithms using diverse topography and image datasets[J]. Planetary and Space Science, 59, 111-131(2011).

    [24] Bandeira L, Ding W, Stepinski T F. Detection of sub-kilometer craters in high resolution planetary images using shape and texture features[J]. Advances in Space Research, 49, 64-74(2012).

    [25] Robbins S J, Hynek B M. A new global database of Mars impact craters ≥1 km: 2. Global crater properties and regional variations of the simple-to-complex transition diameter[J]. Journal of Geophysical Research: Planets, 117, E06001(2012).

    [26] Robbins S J, Hynek B M. A new global database of Mars impact craters ≥1 km: 1. Database creation, properties, and parameters[J]. Journal of Geophysical Research: Planets, 117, E05004(2012).

    [27] Salamunićcar G, Lončarić S, Pina P et al. Integrated method for crater detection from topography and optical images and the new PH9224GT catalogue of Phobos impact craters[J]. Advances in Space Research, 53, 1798-1809(2014).

    [28] Roberto D P, Alfredo R. A robust crater matching algorithm for autonomous vision-based spacecraft navigation[C], 322-327(2021).

    [29] Johnson A, Ansar A, Matthies L et al. A general approach to terrain relative navigation for planetary landing[C], 2854(2007).

    [30] Ding M, Li H B, Cao Y F et al. Research survey of passive image-based impact crater detection[J]. Journal of Deep Space Exploration, 2, 195-202(2015).

    [31] Liu Y X, Liu J J, Mu L L et al. A review of impact-crater detection[J]. Astronomical Research & Technology, 9, 203-212(2012).

    [32] Delatte D M, Crites S T, Guttenberg N et al. Automated crater detection algorithms from a machine learning perspective in the convolutional neural network era[J]. Advances in Space Research, 64, 1615-1628(2019).

    [33] Denevi B W, Chabot N L, Murchie S L et al. Calibration, projection, and final image products of MESSENGER’s mercury dual imaging system[J]. Space Science Reviews, 214, 2(2018).

    [34] Wagner R, Speyerer E, Robinson M et al. New mosaicked data products from the LROC team[EB/OL]. https://www.hou.usra.edu/meetings/lpsc2015/eposter/1473.pdf

    [35] Salamunićcar G, Lončarić S. Open framework for objective evaluation of crater detection algorithms with first test-field subsystem based on MOLA data[J]. Advances in Space Research, 42, 6-19(2008).

    [36] Cheng Y, Miller J K. Autonomous landmark based spacecraft navigation system[EB/OL]. https://trs.jpl.nasa.gov/handle/2014/6432

    [37] Hanak F C. Lost in low lunar orbit crater pattern detection and identification[D](2009).

    [38] Yu M, Cui H T, Tian Y. A new approach based on crater detection and matching for visual navigation in planetary landing[J]. Advances in Space Research, 53, 1810-1821(2014).

    [39] Trigo G F, Maass B, Krüger H et al. Hybrid optical navigation by crater detection for lunar pin-point landing: trajectories from helicopter flight tests[J]. CEAS Space Journal, 10, 567-581(2018).

    [40] Maass B, Woicke S, Oliveira W M et al. Crater navigation system for autonomous precision landing on the moon[J]. Journal of Guidance, Control, and Dynamics, 43, 1414-1431(2020).

    [41] Chen Z H, Jiang J. Crater detection and recognition method for pose estimation[J]. Remote Sensing, 13, 3467(2021).

    [42] Doppenberg W. Autonomous lunar orbit navigation with Ellipse R-CNN[D](2021).

    [43] He J. Research on crater matching based navigation method for lunar precise landing[D](2010).

    [44] Leroy B, Medioni G, Johnson E. Crater detection for autonomous landing on asteroids[J]. Image and Vision Computing, 19, 787-792(2001).

    [45] Chapman C R, Dellenback S W, Enke B et al. Automated identification of Martian craters using image processing[EB/OL]. https://www.lpi.usra.edu/meetings/lpsc2003/pdf/1756.pdf

    [46] Sawabe Y, Matsunaga T, Rokugawa S. Automated detection and classification of lunar craters using multiple approaches[J]. Advances in Space Research, 37, 21-27(2006).

    [47] Sadhukhan P, Palit S. Fast autonomous crater detection by image analysis-for unmanned landing on unknown terrain[M]. Mansouri A, Nouboud F, Chalifour A, et al. Image and Signal Processing. Lecture notes in computer science, 9680, 293-303(2016).

    [48] Gao X Z. Research on lander position and attitude determination based on crater fitting ellipse for precision landing[D](2016).

    [49] Sood R, Chappaz L, Melosh H J et al. Detection and characterization of buried lunar craters with GRAIL data[J]. Icarus, 289, 157-172(2017).

    [50] Zhou Y, Zhao H, Chen M et al. Automatic detection of lunar craters based on DEM data with the terrain analysis method[J]. Planetary and Space Science, 160, 1-11(2018).

    [51] Wetzler P G, Honda R, Enke B et al. Learning to detect small impact craters[C], 178-184(2007).

    [52] Wang H, Jiang J, Zhang G J. CraterIDNet: an end-to-end fully convolutional neural network for crater detection and identification in remotely sensed planetary images[J]. Remote Sensing, 10, 1067(2018).

    [53] Ronneberger O, Fischer P, Brox T. U-Net: convolutional networks for biomedical image segmentation[M]. Navab N, Hornegger J, Wells W M, et al. International conference on medical image computing and computer-assisted intervention-MICCAI 2015. Lecture notes in computer science, 9351, 234-241(2015).

    [54] Szegedy C, Liu W, Jia Y Q et al. Going deeper with convolutions[C](2015).

    [55] Girshick R. Fast R-CNN[C], 1440-1448(2016).

    [56] Ren S Q, He K M, Girshick R et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 1137-1149(2017).

    [57] Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition[EB/OL]. https://arxiv.org/abs/1409.1556

    [58] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition[C], 770-778(2016).

    [59] Zeiler M D, Fergus R. Visualizing and understanding convolutional networks[M]. Fleet D, Pajdla T, Schiele B, et al. Computer Vision-ECCV 2014. Lecture notes in computer science, 8689, 818-833(2014).

    [60] Sainath T N, Vinyals O, Senior A et al. Convolutional, Long Short-Term Memory, fully connected Deep Neural Networks[C], 4580-4584(2015).

    [61] Ali-Dib M, Menou K, Jackson A P et al. Automated crater shape retrieval using weakly-supervised deep learning[J]. Icarus, 345, 113749(2020).

    [62] He K M, Gkioxari G, Dollár P et al. Mask R-CNN[C], 2980-2988(2017).

    [63] Downes L M, Steiner T J, How J P. Lunar terrain relative navigation using a convolutional neural network for visual crater detection[C], 4448-4453(2020).

    [64] Downes L, Steiner T J, How J P. Deep learning crater detection for lunar terrain relative navigation[C], 1838(2020).

    [65] Dong W B, Roy P, Peng C et al. Ellipse R-CNN: learning to infer elliptical object from clustering and occlusion[J]. IEEE Transactions on Image Processing, 30, 2193-2206(2021).

    [66] Kim J R, Muller J P, van Gasselt S et al. Automated crater detection, a new tool for Mars cartography and chronology[J]. Photogrammetric Engineering & Remote Sensing, 71, 1205-1217(2005).

    [67] Martins R, Pina P, Marques J S et al. Crater detection by a boosting approach[J]. IEEE Geoscience and Remote Sensing Letters, 6, 127-131(2009).

    [68] Urbach E R, Stepinski T F. Automatic detection of sub-km craters in high resolution planetary images[J]. Planetary and Space Science, 57, 880-887(2009).

    [69] Viola P, Jones M. Robust real-time face detection[C], 747(2002).

    [70] Emami E, Bebis G, Nefian A et al. Automatic crater detection using convex grouping and convolutional neural networks[M]. Bebis G, Boyle R, Parvin B, et al. Advances in visual computing. Lecture notes in computer science, 9475, 213-224(2015).

    [71] Silburt A, Ali-Dib M, Zhu C C et al. Lunar crater identification via deep learning[J]. Icarus, 317, 27-38(2019).

    [72] Klear M. PyCDA: an open-source library for automated crater detection[EB/OL]. http://www.planetarycraterconsortium.nau.edu/KlearPCC9.pdf

    [73] Lee C, Hogan J. Automated crater detection with human level performance[J]. Computers & Geosciences, 147, 104645(2021).

    [74] Solarna D, Gotelli A, Le Moigne J et al. Crater detection and registration of planetary images through marked point processes, multiscale decomposition, and region-based analysis[J]. IEEE Transactions on Geoscience and Remote Sensing, 58, 6039-6058(2020).

    [75] Christian J A, Derksen H, Watkins R. Lunar crater identification in digital images[EB/OL]. https://arxiv.org/abs/2009.01228

    [76] Hanak C, Crain T, Bishop R. Crater identification algorithm for the lost in low lunar orbit scenario[J]. Advances in the Astronautical Sciences, 137, 2010(2010).

    [77] Park W, Jung Y, Bang H et al. Robust crater triangle matching algorithm for planetary landing navigation[J]. Journal of Guidance, Control, and Dynamics, 42, 402-410(2018).

    [78] Christian J A, Derksen H, Watkins R. Lunar crater identification in digital images[J]. The Journal of the Astronautical Sciences, 68, 1056-1144(2021).

    [79] Xu L H, Jiang J, Ma Y. Ellipse crater recognition for lost-in-space scenario[J]. Remote Sensing, 14, 6027(2022).

    [80] Bandeira L, Saraiva J, Pina P. Impact crater recognition on Mars based on a probability volume created by template matching[J]. IEEE Transactions on Geoscience and Remote Sensing, 45, 4008-4015(2007).

    [81] Feng J H, Cui H T, Cui P Y et al. Autonomous crater detection and matching on planetary surface[J]. Acta Aeronautica et Astronautica Sinica, 31, 1858-1863(2010).

    [82] Shao W, Xie J C, Cao L et al. Crater matching algorithm based on feature descriptor[J]. Advances in Space Research, 65, 616-629(2020).

    [83] Barata T, Alves E I, Saraiva J et al. Automatic recognition of impact craters on the surface of Mars[M]. Campilho A, Kamel M. Image Analysis and Recognition. Lecture notes in computer science, 3212, 489-496(2004).

    [84] Clerc S, Spigai M, Simard-Bilodeau V. A crater detection and identification algorithm for autonomous lunar landing[J]. IFAC Proceedings Volumes, 43, 527-532(2010).

    [85] Lu T T, Hu W D, Liu C et al. Relative pose estimation of a lander using crater detection and matching[J]. Optical Engineering, 55, 023102(2016).

    [86] Yu M. Research on autonomous visual navigation method for planetary landing and exploration mission[D](2016).

    [87] Mortari D, Samaan M A, Bruccoleri C et al. The pyramid star identification technique[J]. Navigation, 51, 171-183(2004).

    [88] Gao X, Zhang T, Liu Y[M]. Fourteen lectures on visual SLAM: from theory to practice, 17-22(2017).

    [89] Cui P Y, Gao X Z, Zhu S Y et al. Progress in complex topography feature matching and autonomous navigation for planetary landing[J]. Journal of Astronautics, 43, 713-722(2022).

    [90] Zhu S Y, Xiu Y, Zhang N et al. Crater-based attitude and position estimation for planetary exploration with weighted measurement uncertainty[J]. Acta Astronautica, 176, 216-232(2020).

    [91] Ma X D, Lü H, Zhang J et al. Research on autonomous landing of fixed wing UAV based on binocular vision[J]. Journal of Ordnance Equipment Engineering, 40, 193-198(2019).

    [92] Sharp C S, Shakernia O, Sastry S S. A vision system for landing an unmanned aerial vehicle[C], 1720-1727(2003).

    [93] Cheng Y, Goguen J, Johnson A et al. The Mars exploration rovers descent image motion estimation system[J]. IEEE Intelligent Systems, 19, 13-21(2004).

    [94] Zhu S Y, Cui P Y, Cui H T et al. Autonomous position and attitude determination for interplanetary landers based on landmark observation angles[J]. Acta Aeronautica et Astronautica Sinica, 31, 318-326(2010).

    [95] Shao W, Wang B N, Dou L F et al. Visual navigation algorithm for asteroid lander based on irregular curve matching[J]. Scientia Sinica: Physica, Mechanica & Astronomica, 52, 83-93(2022).

    [96] Wokes D, Wokes S. Surveying and pose estimation of a lander using approximative crater modelling[C], 8342(2010).

    [97] Li M Y, Mourikis A I. High-precision, consistent EKF-based visual-inertial odometry[J]. The International Journal of Robotics Research, 32, 690-711(2013).

    [98] Gao X S, Hou X R, Tang J L et al. Complete solution classification for the perspective-three-point problem[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25, 930-943(2003).

    [99] Lepetit V, Moreno-Noguer F, Fua P. EPnP: an accurate O(n) solution to the PnP problem[J]. International Journal of Computer Vision, 81, 155-166(2009).

    [100] Penate-Sanchez A, Andrade-Cetto J, Moreno-Noguer F. Exhaustive linearization for robust camera pose and focal length estimation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35, 2387-2400(2013).

    [101] Arun K S, Huang T S, Blostein S D. Least-squares fitting of two 3-D point sets[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 9, 698-700(1987).

    [102] Eggert D W, Lorusso A, Fisher R B. Estimating 3-D rigid body transformations: a comparison of four major algorithms[J]. Machine Vision and Applications, 9, 272-290(1997).

    [103] Alsadat S M, Laurendeau D. Analysis of camera pose estimation using 2D scene features for augmented reality applications[M]. Mansouri A, Moataz A E, Nouboud F, et al. Image and signal processing. Lecture notes in computer science, 10884, 243-251(2018).

    [104] Demmel N, Sommer C, Cremers D et al. Square root bundle adjustment for large-scale reconstruction[C], 11718-11727(2021).

    [105] Lin S Q, Wang J K, Zhao H et al. A survey of visual localization methods based on multiple environmental features[C], 402-406(2021).

    [106] Kim P, Coltin B, Alexandrov O et al. Robust visual localization in changing lighting conditions[C], 5447-5452(2017).

    [107] Feng J H. Research on autonomous optical navigation for pinpoint lunar soft landing[D](2010).

    [108] Kalman R E. A new approach to linear filtering and prediction problems[J]. Journal of Basic Engineering, 82, 35-45(1960).

    [109] Wang Q Z. Study on optical navigation of asteroid lander under poor illumination[D](2020).

    [110] Wang X Y. Reseach on autonomous navigation technology of small celestial body detection landing segment[D](2022).

    [111] Zaritskii V, Svetnik V, Šimelevič L. Monte-Carlo technique in problems of optimal information processing[J]. Avtomatika i telemekhanika, 95-103(1975).

    [112] Handschin J E, Mayne D Q. Monte Carlo techniques to estimate the conditional expectation in multi-stage non-linear filtering[J]. International Journal of Control, 9, 547-559(1969).

    [113] Smith A F M, Gelfand A E. Bayesian statistics without tears: a sampling-resampling perspective[J]. The American Statistician, 46, 84-88(1992).

    [114] Julier S J, Uhlmann J K. Unscented filtering and nonlinear estimation[J]. Proceedings of the IEEE, 92, 401-422(2004).

    [115] Singh L, Lim S. On lunar on-orbit vision-based navigation: terrain mapping, feature tracking driven EKF[C], 6834(2008).

    [116] Xu C, Wang D Y, Huang X Y. Landmark-based autonomous navigation for pinpoint planetary landing[J]. Advances in Space Research, 58, 2313-2327(2016).

    [117] Theil S, Ammann N, Andert F et al. ATON (Autonomous Terrain-based Optical Navigation) for exploration missions: recent flight test results[J]. CEAS Space Journal, 10, 325-341(2018).

    [118] Yu M, Li S, Wang S Q et al. Single crater-aided inertial navigation for autonomous asteroid landing[J]. Advances in Space Research, 63, 1085-1099(2019).

    Liheng Xu, Jie Jiang, Yan Ma. Review of Visual Navigation Technology Based on Craters[J]. Laser & Optoelectronics Progress, 2023, 60(11): 1106013
    Download Citation