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根据目前国内外在可变智能桁架取得的进展,可以对其发展趋势进行展望。
(1)由少自由度发展为多自由度
在ATLAST-9.2 m空间望远镜AAReST项目中,通过少自由度的可变智能桁架应用在次镜支撑上仅具有定位功能,并不具有调整功能。而后出现的通过六自由度和冗余可变智能桁架应用于在轨组装和光学装调中,自由度的提升使该桁架的应用场景更加广泛。在自由度增多的同时,使运动学约束变化及动力学变得更加复杂,因此对控制方法提出了更严格的要求。
(2)由地面装调发展为在轨装调检测
JWST在主镜的安装是通过可变智能桁架在地面进行实现的。而RAMST桁架的展开以及主镜拼接等工作均需要实现无人值守的自动化在轨组装工作,这使得任务的复杂程度提高。同时地面的检测手段并不适用于空间工作,如JWST在地面使用激光跟踪仪检测并对子镜间的位置误差反馈,在轨组装时难以应用。因此科研人员对曲率传感技术等反馈方法进行研究并应用在空间卫星和望远镜的组装工作中。望远镜嵌合式可变智能桁架和可变智能桁架辅助装调之间的区别也越来越模糊。
(3)单一检测与控制方法发展为多种方法融合
装调任务难度和要求的提高、系统精度的提升对检测与控制方法提出了更高的要求。机器视觉精度可达毫米级,坐标测量精度可达微米级,而光学手段可达亚微米到微米级。为了实现系统大范围的高精度控制,一般采用多方法的融合手段。同时,融合了深度学习的控制方法也受到广泛研究,以应对更为复杂的工作,实现轨迹规划和更高的控制精度。机器视觉、曲率传感及波前传感等方法在在轨组装和光学装调中也得到了广泛应用。
在完全自主在轨服务中,航天器在人工智能的支持下不依赖地面测控,仅依靠自身传感器和控制装置就能自主地完成相关操作,具有更高的灵活性,是未来的发展趋势。在轨服务操作涉及到的关键技术主要有测量与感知、决策与规划、操作与控制、学习与适应、多智能体等。目前在轨服务操作关键技术的发展现状和趋势如表1所示。
表 1 计算机辅助装调关键技术现状与趋势
Table 1. Current status and trend of key technologies for computer aided adjustment
Key technology Development status Trends Measurement and perception Force feedback Perception and measurement based on multi-method fusion,
high-speed and high-precision scene reconstructionDecision and planning Model-based autonomous trajectory planning and human-based auxiliary decision-making Autonomous learning and decision-making in a complex dynamic environment Operation and control Autonomous, supervised, cooperative target grabbing, plugging, and other operations Multi-parameter fusion control based on force and vision Learn and adapting Manually extract features to determine the planning and control of the environment Autonomous extraction of features, trajectory planning, perception and control based on self-learning Intelligence Multi-truss control Multi-truss control based on distributed and collaborative learning
Application of variable intelligent trusses in large aperture optical telescopes
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摘要: 可变智能桁架在光学设备装调与在轨组装与维护等方面均有着巨大的优势,针对可变智能桁架在大口径光学设备上的相关技术及应用进行了归纳总结,并对其未来发展趋势进行了展望。首先,针对少自由度串联构型的桁架论述了关于望远镜嵌合式可变智能桁架设计及其应用;之后,着重介绍了可变智能桁架在望远镜在轨组装、调节以及在轨服务中的应用。针对其自由度与定位精度高的特点,总结了智能桁架调节时可使用的反馈方法并对可变智能桁架的结构与控制算法进行了论述;最后,对目前应用于智能桁架的技术进行了总结,并对未来的发展趋势进行了展望。
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关键词:
- 大口径望远镜 /
- 在轨装调 /
- 可变智能桁架 /
- 计算机辅助装调反馈方法
Abstract: Variable intelligent trusses have great advantages in optical equipment and on-orbit assembly. The relevant applications and the development of variable intelligent trusses on large-aperture optical equipment were summarized. Firstly, for serial configuration with less degrees of freedom, the design and application of variable intelligent trusses applied on telescopes were discussed; then, the application of the variable intelligent trusses in the on-orbit assembly, service and adjustment of the telescope were introduced. In view of its high degree of freedom and high positioning accuracy, the feedback methods that could be used in the adjustment of the trusses were summarized, the structure and control algorithm of the trusses were discussed as well. Finally, the technologies currently applied to smart trusses were summarized and the development trend was summarized. -
表 1 计算机辅助装调关键技术现状与趋势
Table 1. Current status and trend of key technologies for computer aided adjustment
Key technology Development status Trends Measurement and perception Force feedback Perception and measurement based on multi-method fusion,
high-speed and high-precision scene reconstructionDecision and planning Model-based autonomous trajectory planning and human-based auxiliary decision-making Autonomous learning and decision-making in a complex dynamic environment Operation and control Autonomous, supervised, cooperative target grabbing, plugging, and other operations Multi-parameter fusion control based on force and vision Learn and adapting Manually extract features to determine the planning and control of the environment Autonomous extraction of features, trajectory planning, perception and control based on self-learning Intelligence Multi-truss control Multi-truss control based on distributed and collaborative learning -
[1] Fan Wenqiang, Wang Zhichen, Chen Baogang, et al. Review of the active control technology of large aperture ground telescopes with segmented mirrors [J]. Chinese Optics, 2020, 13(6): 1195-1208. (in Chinese) [2] Paul A L, Charles A, Mark C, et al. James Webb Space Telescope: Large deployable cryogenic telescope in space [J]. Optical Engineering, 2012, 50(1): 011003. [3] Bin M, Yi H, Zhaohui S, et al. Automation of the AST3 optical sky survey from Dome A, Antarctica [J]. Monthly Notices of the Royal Astronomical Society, 2020, 496: 2768-2775. doi: 10.1093/mnras/staa1730 [4] Abdussamatov H, Lapovok Y, Khankov S. The thermal regime of the special space-based lunar telescope STL-200 for monitoring variations of the global albedo of the earth from the earthshine of the moon[J]. Journal of Optical Technology, 2014, 81(7): 382-387. [5] Allison Y, Youngblood A, Arney G N. The hubble space telescope's near-UV and optical transmission spectrum of earth as an exoplanet [J]. The Astronomical Journal, 2020, 160(3): 100. doi: 10.3847/1538-3881/aba0b4 [6] Tiffany G, Joshua L, Till L, et al. Alignment of the James Webb space telescope optical telescope element [C]//Proc of SPIE, 2016, 9904: 99043Z. [7] Paul R, Charlie A, Larry G. Design and development of the primary and secondary mirror deployment systems for the cryogenic JWST [C]//Proc of the 37th Aerospace Mechanisms Symposium, 2004: 29-44. [8] Redding D C, Feinberg L, Postman M, et al. Beyond JWST: Performance requirements for a future large UVOIR space telescope [C]//Proc of SPIE, 2014, 9413: 914312. [9] William R O, Lee D F, Lloyd R P. ATLAST-9.2 m: a large-aperture deployable space telescope [C]//Proc of SPIE, 2010, 7731: 77312M. [10] Craig U. Autonomous Assembly of a Reconfiguarble Space Telescope (AAReST)-A CubeSat/Microsatellite based technology demonstrator [C]//27th Annual AIAA/USU Conference on Small Satellites, 2013: 1-7. [11] Lee D F, Ritva K, Charlie A, et al. James Webb Space Telescope (JWST) Optical Telescope Element (OTE) pathfinder status and plans [C]//Proc of SPIE, 2014, 9143: 91430E. [12] Nicolas L, Paul B, Joel B. Architecture for in-space robotic assembly of a modular space telescope [J]. Journal of Astronomical Telescopes, Instruments, and Systems, 2016, 2(4): 041207. doi: 10.1117/1.JATIS.2.4.041207 [13] Cheng Zhengai, Hou Xinbin, Zhang Xinghua, et al. In-orbit assembly mission for the Space Solar Power Station [J]. Acta Astronautica, 2016, 129: 299-308. doi: 10.1016/j.actaastro.2016.08.019 [14] Wang Rui, Wang Fuguo, Hao Liang, et al. Research on degree of freedom of secondary mirror truss mechanism based on screw theory and geometry algebra applied on large telescopes [J]. Optik, 2020, 224: 165474. doi: 10.1016/j.ijleo.2020.165474 [15] Wang Rui, Wang Fuguo, Hao Liang, et al. Posture optimization of a 3-6R parallel mechanism for secondary mirror truss applied on large telescopes [J]. Optik, 2020, 227: 165520. [16] Angel F, Ou M, Khanh P, et al. A review of space robotics technologies for on-orbit servicing [J]. Progress in Aerospace Sciences, 2014, 68: 1-26. doi: 10.1016/j.paerosci.2014.03.002 [17] Hari N, Khaled A, Andrew A. Space robotics technologies for deep well operations [C]//Offshore Technology Conference, 2012: 22989. [18] Hrishik M, Phillip S. Motion and parameter estimation for the robotic capture of a non-cooperative space target considering egomotion uncertainty [C]//14th Symposium on Advanced Space Technologies in Robotics and Automation, 2017. [19] Jakob S, Frank K. Space robotics: An overview of challenges, applications and technologies [J]. Kunstliche Intelligenz, 2014, 28: 71-76. [20] Martin K, Thomas A S, Hauke S, et al. Building block-based "iBOSS" approach: Fully modular systems with standard interface to enhance future satellites [C]//66rd International Astronautical Congress, 2015. [21] Rutkovsky V, Sukhanov V, Glumov V. Free-flying manipulation robot using for in-orbit assembly of large space structures [C]//International Conference on Recent Advances in Space Technologies, IEEE, 2011: 808-813. [22] Nishida S, Yoshikawa T. A new end-effector for on-orbit assembly of a large reflector [C]//International Conference on Control, 2006: 1-6. [23] Ozaki F, Machida K. Robot control strategy for in-orbit assembly of a micro satellite [J]. Advanced Robotics, 2004, 18(2): 199-222. doi: 10.1163/156855304322758024 [24] Burge J H, Su P, Zhao C Y, et al. Use of a commercial laser tracker for optical alignment [C]//Proceedings of SPIE, 2007, 6676: 66760E. [25] Liu Fengwei, Wu Yongqian, Chen Qiang, et al. Overview of advanced manufacturing technology of large-aperture aspheric mirror [J]. Opto-Electronic Engineering, 2020, 47(10): 200203. (in Chinese) doi: 10.12086/oee.2020.200203 [26] Zhang Lei, Liu Dong, Shi Tu, et al. Optical free-form surfaces testing technologies [J]. Chinese Optics, 2017, 10(6): 283-299. (in Chinese) [27] Nakamura O, Goto M. Four-beam laser interferometry for three-dimensional microscopic coordinate measurement [J]. Applied Optics, 1994, 33(1): 31-36. doi: 10.1364/AO.33.000031 [28] Takasuji T, Goto M, Kurosawa T, et al. The first measurement of a three-dimensional coordinate by use of a laser tracking interferometer system based on trilateration [J]. Measurement Science and Technology, 1998, 9(1): 38. doi: 10.1088/0957-0233/9/1/006 [29] Ma Yixin, Lu Feng, Wang Hongwei, et al. Dynamic measurement gross error detection model of laser tracker based on prior information [J]. Beijing Surveying and Mapping, 2020, 34(11): 1516-1519. (in Chinese) [30] Qiao Guifang, Sun Dalin, Wen Xiulan, et al. Modeling and analysis of sequential multi-lateration measurement system based on single laser tracker for robot calibration [J]. Acta Metrologica Sinica, 2020, 41(11): 1313-1320. (in Chinese) doi: 10.3969/j.issn.1000-1158.2020.11.01 [31] Anderson D S, Burge J H. Swing-arm profilometry of aspherics [C]//Proceedings of SPIE, 1995, 2536: 169-179. [32] Zeng A, Yu K T, Song S, et al. Multi-view self-supervised deep learning for 6d pose estimation in the amazon picking challenge [C]//IEEE International Conference on Robotics and Automation, 2017. [33] Wen Zhuoman, Wang Yanjie, Di Nan, et al. Fast recognition of cooperative target used for position and orientation measurement of space station’s robot arm [J]. Acta Aeronautica et Astronautica Sinica, 2015, 36(4): 1330-1338. (in Chinese) [34] 文婉欣, 张鑫, 白净. 一种基于单目视觉的智能机械臂系统[J]. 石河子科技, 2020, 254(6): 37-39. doi: 10.3969/j.issn.1008-0899.2020.02.018 [35] Hvisc A M, Burge J H. Alignment analysis of four-mirror spherical aberration correctors [C]//Astronomical Telescopes Instrumentation, International Society for Optics and Photonics, SPIE, 2008, 7018: 701819. [36] Cao Yuze, Ma Wen. Application of two step sensitivity matrix method in Cassegrain telescope alignment [J]. Opto-Electronic Engineering, 2020, 47(2): 180536. (in Chinese) doi: 10.12086/oee.2020.180536 [37] Wang Yu, Zhang Xin, Wang Lingjie. Freeform optical system alignment based on artificial neural networks [J]. Acta Optica Sinica, 2013, 33(12): 1211001. (in Chinese) doi: 10.3788/AOS201333.1211001 [38] Liang Qiongxin, Huang Jinlong, Pan Nian, et al. Alignment method of large aperture telescope based on eigen coefficient [J]. Laser & Optoelectronics Progress, 2021, 58(12): 1211001. (in Chinese) [39] Nanos K, Papadopoulos L. On Cartesian motions with singularities avoidance for free-loating space robots [C]//IEEE lnternational Conference on Robotics and Automation, 2012: 6224695. [40] Jia Zhen, Lou Junqiang, Yang Yiling, et al. Experimental identification and servo velocity-based vibration suppression of a rotating flexible manipulator system [J]. Journal of Vibration and Shock, 2020, 39(24): 76-83. (in Chinese) [41] Li Heyu, Lin Tingyu, Zeng Bi. Control method of space manipulator by using reinforcement learning [J]. Aerospace Control, 2020, 38(6): 38-43. (in Chinese) doi: 10.3969/j.issn.1006-3242.2020.06.007 [42] Cheng Jing, Chen Li. Mechanical analysis and calm control of dual-arm space robot for capture a sitellite [J]. Chinese Journal of Theoretical and Applied Mechanics, 2016, 48(4): 823-834. (in Chinese) doi: 10.6052/0459-1879-16-158 [43] Li Shuo, Li Xixing, Zhao Yan. Optimization of trajectory tracking control in task space for dual-arm space robot [J]. Journal of Mechanical Transmission, 2020, 44(10): 80-85. (in Chinese) [44] Hu Ruixin, Long Changyu, Zhang Lijian. Robotic assembly technology for satellite component based on visual and force information [J]. Optics and Precision Engineering, 2018, 26(10): 2505-2515. (in Chinese) [45] Ai Haiping, Chen Li. Force/position control of dual-arm space robot capture spacecraft [J]. Journal of Harbin Engineering University, 2020, 41(12): 7. (in Chinese) doi: 10.11990/jheu.201812041 [46] Leutenegger S. BRISK: Binary robust invariant scalable keypoint [C]//Proceedings of the 13th IEEE International Conference on Computer Vision, 2011: 2548-2555. [47] Strecha C, Bronstein A, Bronstei M, et al. LDAHash improved matching with smaller descriptors[J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 2012, 34(1): 66-78.