Intelligent Guidance, Navigation, and Control for Next-Generation Spacecraft
A special issue of Aerospace (ISSN 2226-4310). This special issue belongs to the section "Astronautics & Space Science".
Deadline for manuscript submissions: 30 September 2026 | Viewed by 16
Special Issue Editors
2. Shanghai Frontier Science Center for Gravitational Wave Detection, Shanghai 200240, China
Interests: spacecraft navigation; guidance and control; aerospace system engineering technology; space science and deep space exploration; spacecraft space rendezvous and docking and formation flight control; high-speed re-entry spacecraft dynamics and control; intelligent satellite constellation management and control
Interests: spacecraft dynamics and control; attitude control; orbit control; fault diagnosis and fault-tolerant control; control allocation; intelligent space mission planning and task allocation
Special Issues, Collections and Topics in MDPI journals
Interests: micro-/nano-satellite system design; spacecraft mission planning and scheduling; on-orbit servicing (OOS); large-scale satellite constellations; AI algorithm applications in space
Special Issue Information
Dear Colleagues,
Spacecraft guidance, navigation, and control (GNC) is entering a new era driven by the integration of artificial intelligence, autonomous decision-making, and multi-agent coordination. As space missions become increasingly complex, spanning intelligent satellite constellations, on-orbit servicing with space robotics, high-speed atmospheric re-entry, and deep-space exploration, traditional GNC frameworks must evolve to incorporate advanced intelligent methodologies while preserving theoretical rigor and mission reliability.
This Special Issue of Aerospace invites high-quality contributions that bridge rigorous GNC theory with advanced intelligent approaches. Topics of interest include reinforcement learning for autonomous trajectory planning, neural network-based fault diagnosis and reconfiguration, geometric control of free-floating space manipulators, the distributed coordination of large-scale satellite swarms, AI-enhanced re-entry guidance under uncertainty, and hardware-in-the-loop validation of intelligent GNC algorithms.
We particularly encourage submissions that demonstrate a balance between algorithmic innovation and system-level robustness, such as stability-guaranteed learning control, explainable AI for space autonomy, or flight-relevant simulations. Original research articles, comprehensive reviews, and application-oriented case studies from both theoretical and experimental perspectives are welcome.
Prof. Dr. Shufan Wu
Dr. Qiang Shen
Dr. Yixin Huang
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Aerospace is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- intelligent spacecraft GNC
- reinforcement learning in aerospace control
- spacecraft space rendezvous and docking
- intelligent satellite constellation control
- fault-tolerant and adaptive GNC
- geometric mechanics and attitude control
- multi-agent cooperative control in space
- high-speed re-entry guidance and dynamics
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