深空探测器自主技术发展现状与趋势
收稿日期: 2013-05-02
修回日期: 2013-07-04
网络出版日期: 2013-07-19
基金资助
国家“973”计划（2012CB720000）；国家自然科学基金（60803051，60874094）；高等学校博士学科点专项科研基金（20111101110001）；北京理工大学科技创新团队资助项目
State of the Art and Development Trends of On-board Autonomy Technology for Deep Space Explorer
Received date: 2013-05-02
Revised date: 2013-07-04
Online published: 2013-07-19
Supported by
National Basic Research Program of China (2012CB720000); National Natural Science Foundation of China (60803051, 60874094); Research Fund for the Doctoral Program of Higher Education of China (20111101110001); Project of BIT Science and Technology Innovation Team
深空探测器距离地球远、所处环境复杂、苛刻，利用地面测控站进行深空探测器的遥测和遥控已经很难满足探测器控制的实时性和安全性要求。深空探测器自主技术即通过在探测器上构建一个智能自主管理软件系统，自主地进行工程任务与科学任务的规划调度、命令执行、星上状态的监测与故障时的系统重构，完成无人参与情况下的探测器长时间自主安全运行，自主技术已经逐渐成为深空探测领域未来发展的一项关键技术。本文首先分析了传统测控模式对深空探测的约束，回顾了深空探测器自主技术发展的现状，分析了实现深空探测器自主运行的关键技术，包括在轨自主管理系统设计技术、自主任务规划技术、自主导航与控制技术、自主故障处理技术和自主科学任务操作技术。然后结合深空探测工程实施和技术发展需求，提出未来深空探测器自主技术发展的趋势和重点。
崔平远 , 徐瑞 , 朱圣英 , 赵凡宇 . 深空探测器自主技术发展现状与趋势[J]. 航空学报, 2014 , 35(1) : 13 -28 . DOI: 10.7527/S1000-6893.2013.0335
During the process of deep space exploration, the explorer is far away from the Earth while the environment around it is complex and harsh. Therefore it is difficult for ground stations with telecontrol and telemetry to satisfy the real-time and safety requirements of control systems for the deep space explorer. Autonomy technology then becomes a key to deep space exploration. An on-board autonomous management software system is used to enable the planning and scheduling of engineering and science tasks, execute commands, monitor states of the explorer and reconfigue the system when faults arise, all of which guarantees the autonomous and safe on-board operation without commands from the ground in the long cause of exploration. This paper first analyzed the limits of the traditional measuring and controlling mode for deep space exploration and reviewed the state of the art of autonomy technology. Then, it analyzed the key techniques of the autonomy of the explorer, which consisted of on-board autonomous management system designing, autonomous mission planning, autonomous navigation and control, autonomous fault processing and recovery, and autonomous operation of scientific mission. Finally, combined with the engineering implementation and technology requirements of deep space exploration, the paper envisaged the development trends and key points of autonomous technology of deep space explorers in future.
[1] Gomez M. A typical spacecraft autonomy system[C]//IMCL Workshop on Machine Learning for Autonomous Space Applications, 2003.
[2] Cancro G J. APL spacecraft autonomy: then, now, and tomorrow[J]. Johns Hopkins APL Technical Digest, 2010, 29(3): 226-233.
[3] Atkinson D J, Smith B D. Autonomy technology at JPL[C]//Proceedings of the 6th International Symposium on Artificial Intelligence, Robotics and Automation in Space, 2001.
[4] Pell B, Bernard D E, Chien S A, et al. An autonomous spacecraft agent prototype[J]. Autonomous Robots, 1998, 5(1): 29-52.
[5] Bermyn J. PROBA—project for on-board autonomy[J]. Air & Space Europe, 2000, 2(1): 70-76.
[6] Teston F, Creasey R, Bermyn J, et al. PROBA: ESA's autonomy and technology demonstration mission[C]//The 13th Annual AIAA/USU Conference on Small Satellites, 1999.
[7] Gantois K, Teston F, Montenbruck O, et al. PROBA-2 mission and new technologies overview[C]//Small Satellite Systems and Services—the 4S Symposium, 2006.
[8] Chu Y H, Wang D Y, Huang X Y. Observability analysis based information fusion integrated navigation[J]. Aerospace Control, 2011, 29(2): 31-36. (in Chinese) 褚永辉, 王大轶, 黄翔宇. 基于能观度分析的信息融合组合导航方法研究[J]. 航天控制, 2011, 29(2): 31-36.
[9] Gong J, Yang H, Zhao W, et al. Knowledge inference based self fault diagnosis method for spacecraft[J]. Aerospace Control and Application, 2011, 37(4): 19-23. (in Chinese) 龚健, 杨桦, 赵玮, 等. 基于知识推理的航天器自主故障诊断方法[J]. 空间控制技术与应用, 2011, 37(4): 19-23.
[10] Li Z B, Wu H X, Xie Y C, et al. Experimental platform for spacecraft intelligent control[J]. Acta Automatica Sinica, 2001, 27(5): 695-699. (in Chinese) 李智斌, 吴宏鑫, 谢永春, 等. 航天器智能控制实验平台[J]. 自动化学报, 2001, 27(5): 695-699.
[11] Dai S W, Sun H X. Autonomous control for spacecraft[J]. Chinese Journal of Space Science, 2002, 22(2): 147-153. (in Chinese) 代树武, 孙辉先. 卫星运行中的自主控制技术[J]. 空间科学学报, 2002, 22(2): 147-153.
[12] Li B Q, Li X Z, Wang H F, et al. Mission planning method of the greedy algorithm and dynamic programming[J]. Microelectronics & Computer, 2013, 30(2): 144-147. (in Chinese) 李博权, 李绪志, 王红飞, 等. 贪婪算法与动态规划结合的任务规划方法[J]. 微电子学与计算机, 2013, 30(2): 144-147.
[13] Pan Z S, Meng X, Zheng J H, et al. Research on simulation elements of space missions demonstration platform[J]. Journal of System Simulation, 2012, 24(7): 1366-1372. (in Chinese) 潘忠石, 孟新, 郑建华, 等. 空间任务论证平台仿真要素研究[J]. 系统仿真学报, 2012, 24(7): 1366-1372.
[14] Huang H B, Ma G F, Zhuang Y F, et al. Real-time re-planning for satellite formation reconfiguration in deep space[J]. Journal of Astronautics, 2012, 33(3): 325-333. (in Chinese) 黄海滨, 马广富, 庄宇飞, 等. 深空环境下卫星编队飞行队形重构实时重规划[J]. 宇航学报, 2012, 33(3): 325-333.
[15] Chen Y W, Yao F, Li J F, et al. A learnable ant colony optimization to the mission planning of multiple satellites[J]. Systems Engineering-Theory & Practice, 2013, 33(3): 791-801. (in Chinese) 陈英武, 姚锋, 李菊芳, 等. 求解多星任务规划问题的演化学习型蚁群算法[J]. 系统工程理论实践, 2013, 33(3): 791-801.
[16] Sun K, Bai G Q, Chen Y W, et al. Action planning for agile earth-observing satellite mission planning problem[J]. Journal of National University of Defense Technology, 2012, 34(6): 141-147. (in Chinese) 孙凯, 白国庆, 陈英武, 等. 面向动作序列的敏捷卫星任务规划问题[J]. 国防科技大学学报, 2012, 34(6): 141-147.
[17] Xu R, Cui P Y, Xu X F. Realization of multi-agent planning system for autonomous spacecraft[J]. Advances in Engineering Software, 2005, 36(4): 266-272.
[18] Xu R, Cui P Y, Xu X F. Design for autonomous mission planning system[J]. Aircraft Engineer and Aerospace Technology: An International Journal, 2003, 75(4): 365-371.
[19] Wu H X, Hu H X, Xie Y C, et al. Several questions on autonomous rendezvous docking[J]. Journal of Astronautics, 2003, 24(2): 132-137, 143. (in Chinese) 吴宏鑫, 胡海霞, 谢永春, 等. 自主交会对接若干问题[J]. 宇航学报, 2003, 24(2): 132-137, 143.
[20] Cui H T, Cheng X J, Xu R, et al. RHC-based attitude control of spacecraft under geometric constraints[J]. Aircraft Engineering and Aerospace Technology, 2011, 83(5): 296-305.
[21] Xu R, Cheng X J, Cui H T. Autonomous pointing avoidance of spacecraft attitude maneuver using backstepping control method[M]//Zhu M. Electrical Engineering and Control. Berlin: Springer-Verlag Berlin Heidelberg, 2011: 817-825.
[22] Pell B, Sawyer S R, Muscettola N, et al. Mission operations with an autonomous agent[C]//1998 IEEE Aerospace Conference, 1998, 2: 289-313.
[23] Lee S C, Santo A G. Reducing mission operations costs through spacecraft autonomy: the near earth asteroid rendezvous (NEAR) experience[J]. Journal of Reducing Space Mission Cost, 1998, 1(1): 87-104.
[24] Marshall M H, Low G D. Final report of the autonomous spacecraft maintenance study group, NASA-CR-164076[R]. 1981.
[25] Chiu M C, Von-Mehlem U I, Willey C E, et al. ACE spacecraft[J]. Space Science Reviews, 1998, 86(1-4): 257-284.
[26] Wozniak J J. Vehicle technology at APL[J]. Johns Hopkins APL Technical Digest, 2003, 24(1): 19-30.
[27] Wiley S, Herbert G, Mosher L. Design and development of the NEAR propulsion system, AIAA-1995-2977[R]. Reston: AIAA, 1995.
[28] Rasmussen R D, Singh G, Rathbun D B, et al. Behavioral model pointing on Cassini using target vectors[C]//Proceedings of the Annual Rocky Mountain Guidance and Control Conference, 1995: 91-110.
[29] Singh G, Macala G, Wong E, et al. A constraint monitor algorithm for the Cassini spacecraft, AIAA-1997-3526[R]. Reson: AIAA, 1997.
[30] Chien, S, Doyle R, Davies A G, et al. The future of AI in space[J]. IEEE Intelligent Systems, 2006, 21(4): 64-69.
[31] Rajan K, Shirley M, Taylor W, et al. Ground tools for autonomy in the 21st century[C]//2000 IEEE Aerospace Conference Proceedings, 2000, 7: 649-659.
[32] Cancro G, Innanen W, Turner R, et al. Uploadable executable specification concept for spacecraft autonomy systems[C]//2007 IEEE Aerospace Conference Proceedings, 2007: 1-12.
[33] Turner R, Hooda S, Gersh J, et al. ExecSpec: visually designing and operating a finite state machine-based spacecraft autonomy system[C]//Proceedings of the 9th International Symposium on Artificial Intelligence, Robotics and Automation in Space, 2008.
[34] Steel R, Niezette M, Cesta A, et al. Advanced planning and scheduling initiative: MrSPOCK AIMS for XMAS in the space domain[C]//Proceedings of IJCAI-09 Workshop on Artificial Intelligence in Space, 2009.
[35] Verfaillie G, Infantes G, Lematre M, et al. On-board decision-making on data downloads[C]//The 7th International Workshop on Planning and Scheduling for Space (IWPSS-11), 2011.
[36] Nayak P, Kurien J, Dorais G, et al. Validating the DS-1 remote agent experiment[C]//Proceedings of the 5th International Symposium on Artificial Intelligence, Robotics and Automation in Space, 1999: 349.
[37] Ghallab M, Nau D, Traverso P. Automated planning: theory & practice[M]. Burlington: Morgan Kaufmann, 2004.
[38] Chien S, Smith B, Rabideau G, et al. Automated planning and scheduling for goal-based autonomous spacecraft[J]. IEEE Intelligent Systems and their Applications, 1998, 13(5): 50-55.
[39] Katz D S, Some R R. NASA advances robotic space exploration[J]. Computer, 2003, 36(1): 52-61.
[40] Chien S, Rabideau G, Knight R, et al. ASPEN-automated planning and scheduling for space mission operations[C]//The Six International Conference on Space Operations (SpaceOps 2000), 2000.
[41] Chien S A, Knight R, Stechert A, et al. Using iterative repair to improve the responsiveness of planning and scheduling[C]//Proceedings of the Fifth International Conference on Artificial Intelligence Planning and Scheduling, 2000: 300-307.
[42] Knight S, Rabideau G, Chien S, et al. Casper: space exploration through continuous planning[J]. IEEE Intelligent Systems, 2001, 16(5): 70-75.
[43] Chien S, Sherwood R, Tran D, et al. Lessons learned from autonomous sciencecraft experiment[C]//Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, 2005: 11-18.
[44] European Cooperation for Space Standardization. Space engineering-space segment operability, ECSS-E-70-11[R]. Noordwijk: ESA Publications Division, 2005.
[45] Woods M, Long D, Baldwin L, et al. On-board planning and scheduling for the ExoMars mission[C]//Proceedings of the DASIA, 2006: 22-25.
[46] Mose Sorensen E, Ferri P. Technology driver-the Rosetta mission[C]//IEE 5th CCSDS Workshop on New Technologies, New Standards, 1998: 2/1-2/8.
[47] Pekala M, Cancro G, Moore J. Verifying executable specifications of spacecraft autonomy[C]//Proceedings of the 9th International Symposium on Artificial Intelligence, Robotics and Automation in Space, 2008.
[48] Verfaillie G, Charmeau M C. A generic modular architecture for the control of an autonomous spacecraft[C]//The 5th International Workshop on Planning and Scheduling for Space (IWPSS-06), 2006.
[49] Alami R, Chatila R, Fleury S, et al. An architecture for autonomy[J]. International Journal of Robotics Research, 1998, 17(4): 315-337.
[50] Barrett A. Autonomy architectures for a constellation of spacecraft[C]//Proceedings of the 5th International Symposium on Artificial Intelligence, Robotics and Automation in Space, 1999: 291.
[51] Fesq L, Aljabri A, Anderson C, et al. Spacecraft autonomy in the new millennium[C]//19th Annual AAS Guidance and Control Conference, 1996.
[52] Smith B, Millar W, Dunphy J, et al. Validation and verification of the remote agent for spacecraft autonomy[C]//Proceedings of 1999 IEEE Aerospace Conference, 1999, 1: 449-468.
[53] Low K H, Leow W K, Ang Jr M H. A hybrid mobile robot architecture with integrated planning and control[C]//Proceedings of the 1st International Joint Conference on Autonomous Agents and Multiagent Systems, 2002: 219-226.
[54] Charmeau M C, Bensana E. AGATA: a lab bench project for spacecraft autonomy[C]//Proceedings of the 8th International Symposium on Artificial Intelligence, Robotics and Automation in Space, 2005.
[55] Gregory N M, Dorais G A, Fry C, et al. IDEA: planning at the core of autonomous reactive agents[C]//Proceedings of the 3rd International NASA Workshop on Planning and Scheduling for Space, 2002.
[56] Chien S A, Johnston M, Frank J, et al. A generalized timeline representation, services, and interface for automating space mission operations[C]//The 12th International Conference on Space Operations (SpaceOps 2012), 2012.
[57] Frank J D, Clement B J, Chachere J M, et al. The challenge of configuring model-based space mission planners[C]//The 7th International Workshop on Planning and Scheduling for Space (IWPSS-11), 2011.
[58] Morris P, Schwabacher M, Dalal M, et al. Embedding temporal constraints for coordinated execution in habitat automation[C]//The 8th International Workshop on Planning and Scheduling for Space (IWPSS-13), 2013.
[59] Johnston M D. Spike: AI scheduling for NASA's hubble space telescope[C]//Sixth Conference on Artificial Intelligence Applications, 1990: 184-190.
[60] Museettola N. HSTS: integrating planning and scheduling, CMU-RI-TR-93-05[R]. Pittsburgh: Robotics Institute, Carnegie Mellon University, 1993.
[61] Bedrax-Weiss T, McGann C, Iatauro M. EUROPA2: plan database services for planning and scheduling applications[C]//Workshop of System Demonstration (ICAPS 2005), 2005: 18-19.
[62] Verfaillie G, Pralet C, Lematre M. How to model planning and scheduling problems using constraint networks on timelines[J]. Knowledge Engineering Review, 2010, 25(3): 319.
[63] Ghallab M, Howe A, Knoblock C, et al. PDDL—the planning domain definition language, Tech Report CVC TR-98-003/DCS TR-1165[R]. 1998.
[64] Fox M, Long D. PDDL2.1: an extension to PDDL for expressing temporal planning domains[J]. Journal of Artificial Intelligence Research, 2003, 20: 61-124.
[65] Elachi. C. The critical role of communications and navigation technologies to the success of space science enterprise missions[C]//Keynote Address DESCANSO International Symposium, 1999.
[66] Bhaskaran S, Riedel J E, Synnott S P. Autonomous optical navigation for interplanetary missions[C]//Proceedings of SPIE, 1996, 2810: 32-43.
[67] Desai S, Han D, Bhaskaran S, et al. Autonomous optical navigation[R]. 2001.
[68] Lisman S S, Chang D H, Singh G, et al. Autonomous guidance and control of a solar electric propulsion spacecraft, AIAA-1997-3818[R]. Reston: AIAA, 1997.
[69] Bhaskaran S, Desai S, Dumont P, et al. Orbit determination performance evaluation of the deep space 1 autonomous navigation system[C]//Proceedings of the AAS/AIAA Space Flight Mechanics Meeting, 1998.
[70] Bhat R S, Stumpf P W, Frauenholz R B. Deep impact ground navigation maneuver design and performance[C]//Proceedings of the AAS/AIAA Space Flight Mechanics Meeting, 2006: 123-142.
[71] Uo M, Shirakawa K, Hashimoto T, et al. Hayabusa's touching-down to Itokawa-autonomous guidance and navigation[C]//Proceedings of the AAS/AIAA Space Flight Mechanics Meeting, 2006: 1805-1816.
[72] Froyum K, Goepfert S, Henrickson J, et al. Honeywell micro electro mechanical systems (MEMS) inertial measurement unit (IMU)[C]//2012 IEEE/ION Position Location and Navigation Symposium (PLANS), 2012: 831-836.
[73] Grotzinger J P, Crisp J, Vasavada A R, et al. Mars Science Laboratory mission and science investigation[J]. Space Science Reviews, 2012, 170(1-4): 5-56.
[74] Bregon A, Daigle M, Roychoudhury I. An integrated framework for model-based distributed diagnosis and prognosis[C]//Annual Conference of the Prognostics and Health Management Society, 2012: 416-426.
[75] Pecheur C, Simmons R. From livingstone to SMV[M]//Rash J L, Truszkowski W, Hinchey M G. Formal Approaches to Agent-based Systems. Berlin: Springer-Verlag Berlin Heidelberg, 2001: 103-113.
[76] Hu Q L, Friswell M I, Wagg D J, et al. Adaptive backstepping fault-tolerant control for flexible spacecraft with bounded unknown disturbances[C]//Proceedings of the 48th IEEE Conference on Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference, 2009: 788-793.
[77] Kurtoglu T, Tumer I Y. A graph-based fault identification and propagation framework for functional design of complex systems[J]. Journal of Mechanical Design, 2008, 130(5): 051401.
[78] Kuhn L, de Kleer J, Liu J. Online model-based diagnosis for multiple, intermittent and interaction faults[C]//Annual Conference of the Prognostics and Health Management Society, 2009.
[79] Castano A, Fukunaga A, Biesiadecki J, et al. Automatic detection of dust devils and clouds on Mars[J]. Machine Vision and Applications, 2008, 19(5-6): 467-482.
[80] Thompson D, Niekum S, Smith T, et al. Automatic detection and classification of features of geologic interest[C]//2005 IEEE Aerospace Conference, 2005: 366-377.
[81] Chien S, Sherwood R, Tran D, et al. Using autonomy flight software to improve science return on earth observing one[J]. Journal of Aerospace Computing, Information, and Communication, 2005, 2(4): 196-216.
[82] Castano R, Wagstaff K L, Chien S, et al. On-board analysis of uncalibrated data for a spacecraft at Mars[C]//Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007: 922-930.
[83] Chien S A, Tran D, Rabideau G, et al. Improving the operations of the earth observing one mission via automated mission planning, AIAA-2010-2199[R]. Reston: AIAA, 2010.
[84] Hayden D S, Chien S, Thompson D R, et al. Onboard clustering of aerial data for selective data return[C]//Proceedings of the 10th International Symposium on Artificial Intelligence, Robotics and Automation in Space, 2010.
[85] Thompson D R, Smith T, Wettergreen D. Information-optimal selective data return for autonomous rover traverse science and survey[C]//IEEE International Conference on Robotics and Automation, 2008: 968-973.
[86] Rabideau G, Chien S, McLaren D. Onboard run-time goal selection for autonomous operations, AIAA-2010-2203[R]. Reston: AIAA, 2010.
[87] Rabideau G, Chien S, McLaren D. Tractable goal selection for embedded systems with oversubscribed resources[J]. Journal of Aerospace Computing, Information, and Communication, 2011, 8(5): 151-169.
[88] Hayden D S, Chien S, Thompson D R, et al. Onboard clustering of aerial data for selective data return[C]//Proceedings of the 10th International Symposium on Artificial Intelligence, Robotics and Automation in Space, 2010.
[89] Stottler R. Satellite communication scheduling, optimization, and deconfliction using artificial intelligence techniques[C]//The 11th International Conference on Space Operations (SpaceOps 2010), 2010.
[90] Gerevini A E, Serina I. Efficient plan adaptation through replanning windows and heuristic goals[J]. Fundamenta Informaticae, 2010, 102(3-4): 287-323.
[91] Donati A, Policella N. AI planning and scheduling infusion in space: ESA achievements and perspectives[C]//The 11th International Conference on Space Operations (SpaceOps 2010), 2010.
/
| 〈 |
|
〉 |
CJA