24 October 2017 Enriching mission planning approach with state transition graph heuristics for deep space exploration
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Proceedings Volume 10463, AOPC 2017: Space Optics and Earth Imaging and Space Navigation; 1046308 (2017) https://doi.org/10.1117/12.2282947
Event: Applied Optics and Photonics China (AOPC2017), 2017, Beijing, China
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.
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Hao Jin, Hao Jin, Rui Xu, Rui Xu, Wenming Xu, Wenming Xu, Pingyuan Cui, Pingyuan Cui, Shengying Zhu, Shengying Zhu, } "Enriching mission planning approach with state transition graph heuristics for deep space exploration", Proc. SPIE 10463, AOPC 2017: Space Optics and Earth Imaging and Space Navigation, 1046308 (24 October 2017); doi: 10.1117/12.2282947; https://doi.org/10.1117/12.2282947
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