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Enriching mission planning approach with state transition graph heuristics for deep space exploration
Author(s): Hao Jin; Rui Xu; Wenming Xu; Pingyuan Cui; Shengying Zhu
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Paper Abstract

As to support the mission of Mars exploration in China, automated mission planning is required to enhance security and robustness of deep space probe. Deep space mission planning requires modeling of complex operations constraints and focus on the temporal state transitions of involved subsystems. Also, state transitions are ubiquitous in physical systems, but have been elusive for knowledge description. We introduce a modeling approach to cope with these difficulties that takes state transitions into consideration. The key technique we build on is the notion of extended states and state transition graphs. Furthermore, a heuristics that based on state transition graphs is proposed to avoid redundant work. Finally, we run comprehensive experiments on selected domains and our techniques present an excellent performance.

Paper Details

Date Published: 24 October 2017
PDF: 6 pages
Proc. SPIE 10463, AOPC 2017: Space Optics and Earth Imaging and Space Navigation, 1046308 (24 October 2017); doi: 10.1117/12.2282947
Show Author Affiliations
Hao Jin, Beijing Institute of Technology (China)
Ministry of Industry and Information Technology (China)
Rui Xu, Beijing Institute of Technology (China)
Ministry of Industry and Information Technology (China)
Wenming Xu, Beijing Institute of Technology (China)
Ministry of Industry and Information Technology (China)
Pingyuan Cui, Beijing Institute of Technology (China)
Ministry of Industry and Information Technology (China)
Shengying Zhu, Beijing Institute of Technology (China)
Ministry of Industry and Information Technology (China)


Published in SPIE Proceedings Vol. 10463:
AOPC 2017: Space Optics and Earth Imaging and Space Navigation
Carl Nardell; Suijian Xue; Huaidong Yang, Editor(s)

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