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Prospects for intelligent navigation technologies in deep−space exploration
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Weiren WU1, 2, Zhe ZHANG2, *, Wangwang LIU1, Shiliang WANG1, *, Qier AN3, Tongtong FENG4, Rui XU5, Binfeng PAN3, Wenwu ZHU4
Science & Technology Review | 2026, 44(14) : 56 - 68
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Science & Technology Review | 2026, 44(14): 56-68
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Prospects for intelligent navigation technologies in deep−space exploration
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Weiren WU1, 2, Zhe ZHANG2, *, Wangwang LIU1, Shiliang WANG1, *, Qier AN3, Tongtong FENG4, Rui XU5, Binfeng PAN3, Wenwu ZHU4
Affiliations
  • 1Deep Space Exploration Laboratory, Hefei 230031, China
  • 2Lunar Exploration and Space Engineering Center, Beijing 100190, China
  • 3School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China
  • 4Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
  • 5School of Aerospace Science and Technology, Beijing Institute of Technology, Beijing 100081, China
Published: 2026-07-28 doi: 10.3981/j.issn.1000-7857.2026.06.00005
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Uncrewed deep-space exploration missions operate under extreme constraints, including vast distances, long communication delays, weak signals, and complex dynamical environments, making conventional ground−control architectures increasingly inadequate for long−duration, complex operations. This review systematically examines advances in intelligent navigation for deep−space exploration. It proposes a perception−decision−execution−auxiliary architecture and synthesizes progress and key bottlenecks in critical technologies, including extreme−environment perception and autonomous cognition, multi−source fusion autonomous navigation, mission planning and decision−making under long−delay conditions, intelligent control in complex dynamical environments, and intelligent navigation auxiliary support technologies for deep space, with particular attention to the integration of artificial intelligence and its future development. Building on this analysis, the review outlines priorities for advancing intelligent navigation in deep space, providing a technical reference for the planning and implementation of China's Phase II planetary exploration program, solar−system boundary exploration, and other future deep−space missions.

deep−space exploration  /  intelligent navigation  /  environmental perception  /  intelligent control  /  artificial intelligence
Weiren WU, Zhe ZHANG, Wangwang LIU, Shiliang WANG, Qier AN, Tongtong FENG, Rui XU, Binfeng PAN, Wenwu ZHU. Prospects for intelligent navigation technologies in deep−space exploration[J]. Science & Technology Review, 2026 , 44 (14) : 56 -68 . DOI: 10.3981/j.issn.1000-7857.2026.06.00005
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Article Info
doi: 10.3981/j.issn.1000-7857.2026.06.00005
  • Receive Date：2026-06-01
  • Online Date：2026-08-19
  • Published：2026-07-28
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  • Received：2026-06-01
  • Revised：2026-07-21
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Affiliations
    1Deep Space Exploration Laboratory, Hefei 230031, China
    2Lunar Exploration and Space Engineering Center, Beijing 100190, China
    3School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China
    4Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
    5School of Aerospace Science and Technology, Beijing Institute of Technology, Beijing 100081, China
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多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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