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Modeling of Autonomous Flight Mission Intelligent Planning for Small Body Exploration
- ZHU Liying1, YE Zhiling1, LI Yuqing2, FU Zhongliang3, XU Yong1
Author information
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1. Beijing Institute of Spacecraft system Engingeering, Beijing 100081, China;
2. Dept. Control Engineering, Harbin Institute of Technology, Harbin 150001, China;
3. Lunar Exploration and Space Program Center, Beijing 100190, China
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History
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| Received |
Revised |
| 12 Jul 2019 |
10 Aug 2019 |
| Issue Date |
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| 20 May 2022 |
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The needs for samll body intelligent planning are analuzed due to the significant communication delay and low efficiency of mission execution. The intelligent planning of autonomous flight aroundfor small body exploration mission is studied. Firstly, the problem is decomposed into two parts:platform task intelligent planning and payload task intelligent planning. A knowledge model of detector autonomous management is designed based on PDDL language, and a solution algorithm of specific state time line extension is proposed. The mathematical model of intelligent planning based on CSP is established, and the solving algorithm based on genetic strategy is proposed. Finally, a simulation system is developed to verify the algorithm. The simulation results show that the method can integrate the platform and payload requirements, making unified mission planning under the constraints of storage, energy, communication and other constraints, and obtaining command sequence and action sequence. It can improve the intelligence of task management and control, and reduce the complexity of task operation.
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References
[1] BRESINA J L, JÓNSSON A K, MORRIS P H, et al. Activity planning for the Mars Exploration Rovers[C]//ICAPS2005. Monterey:ICAPS, 2005:40-49.
[2] CESTA A, CORTELLESSA G, FRATINI S, et al. Mr SPOCK-Steps in developing an End-to-End space application[J]. Computational Intelligence, 2011, 27(1):83-102.
[3] AGHEVLI A, BENCOMO A, MC CURDY M. Scheduling and Planning Interface for Exploration (SPIFe)[C]//Proceedings of International Conference on Automated Planning and Scheduling (ICAPS2011). Freiburg:ICAPS, 2011.
[4] JONSSON A, MORRIS P, MUSCETTOLA N, et al. Next generation remote agent planner[C]//Proc. 5th Int. Symposition on AI, Robotics and Automation in Space. USA:[s.n.], 1999.
[5] NILSSON N J. Artificial intelligence:a new synthesis[C]. San Mateo. CA, Morgan Kaufmann:[s.n.] 1998.
[6] 李玉庆,徐敏强,王日新.航天器自主规划系统分析与设计[J].吉林大学学报(工学版), 2007(6):1471-1475. LI Y Q, XU M Q, WANG R. Analysis and design of autonomous con-trol system for spacecraft[J]. Journal of Jilin University (Engineering and Technology Edition), 2007(6):1471-1475.
[7] 王海波,徐敏强,王日新,等.对地观测小卫星星座长期任务规划求解技术[J].系统工程与电子技术, 2011, 33(6):1293-1298. WANG H B, XU M Q, WANG R X, et al. Long-term acquisition plan method for small satellites constellation[J]. Systems Engineer-ing and Electronics, 2011, 33(6):1293-1298.
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