Autonomous Safe Learning of Space Intelligent Systems

Scope

Extraterrestrial space, as the main object for humans to explore the unknown world and carry out exploration activities, has gradually become the focus of research in countries worldwide. The space unmanned system played a crucial role in the whole process. Looking to the future, an intelligent and autonomous space unmanned system is the inevitable trend of subsequent technological development. It will significantly change space exploration missions, detection modes, and detection significance. At the same time, with the rapid development of artificial intelligence technology, the urgent need for independent development of space intelligence is increasingly prominent, attracting more and more people to participate in the research of space intelligence. However, it is undeniable that due to the black-box nature of the neural network, it can still not give a complete explanation or proof in many aspects, such as interpretability, portability, robustness, etc. It is challenging to make it widely used in space missions with high requirements for security. Therefore, how to break through the existing bottleneck and how to provide an intelligent learning system suitable for space missions from a new perspective are the frontier of future development. It will largely determine the boundary of the development of aerospace intelligence. This Special Issue focuses on the safe learning of unmanned space systems and explores how to effectively and safely apply artificial intelligence technology to space missions. We welcome original research contributions and reviews of state-of-the-art studies from academia and industry. The Special Issue topics include, but are not limited to:

• Advanced safe learning theory
• Safe learning interpretability mechanism
• Learning-based multi-agent game and cooperation
• Long-term learning security and stability in the space environment
• Single/Multi-agent safe learning with resilience guarantee
• The application of safe learning in space missions, such as in-orbit services and space transportation, includes but is not limited to satellites, space vehicles, hypersonic vehicles, solar sails, space robots, etc.

Guest Editors

Chengchao Bai, Harbin Institute of Technology

Chengchao Bai, associate professor of the School of Astronautics of Harbin Institute of Technology, has been selected into the Young Elite Scientists Sponsorship Program by CAST and the Young Talents Selection Program of HIT. His research interests include intelligent unmanned systems, multi-agent safe reinforcement learning, large-scale multi-robot collaboration, intelligent game confrontation and decision-making. He served as a member for the Youth Editorial Board of the Journal Unmanned Systems Technology and Aerospace Technology. He is a committee member of the IEEE RAS Technical Committee on Multi-robot Systems, CICC (Chinese Institute of Command and Control) Technical Committee on Unmanned Systems, CAAI (Chinese Association for Artificial Intelligence) Technical Committee on Cognitive Systems and Information Processing, and CSIG (China Society of Image and Graphing) Technical Committee on Machine Vision. He has published more than 40 academic papers in top journals such as Pattern Recognition, IEEE TITS, IEEE TVT, and IEEE TAES.

Zhi Li, Space Engineering University

Zhi Li, Vice President and Chief Education Officer of Space Engineering University, professor, doctoral supervisor, has been engaged in teaching and research work in space safety, target characteristics, spacecraft guidance and control for a long time. He has published 14 books, 24 authorized invention patents, and more than 50 academic papers. His topic has received support from many domestic funds, and his research achievements have received wide attention, which has promoted the development of related fields. He was selected as the national "Ten Thousand Talents Plan" scientific and technological innovation leader, the "New Century Excellent Talent Support Plan" of the Ministry of Education, and the young and middle-aged scientific and technological leader of the Ministry of Science and Technology.

Wei Pan, Delft University of Technology

Wei Pan received the Ph.D. degree in bioengineering from Imperial College London. He is currently an Assistant Professor with the Department of Cognitive Robotics, Delft University of Technology. Until May 2018, he was a Project Leader with DJI, Shenzhen, China, responsible for machine learning research for DJI drones and AI accelerator. His research interests include machine learning, control theory, and robotics. He was a recipient of Dorothy Hodgkin’s Postgraduate Awards, Microsoft Research Ph.D. Scholarship and Chinese Government Award for Outstanding Students Abroad, and Shenzhen Peacock Plan Award. He also serves as the Area Chair for CoRL and an Associate Editor for IROS.

Hantian Zhang, Karlsruhe Institute of Technology

Hantian Zhang is currently a researcher in theoretical particle physics at Karlsruhe Institute of Technology, Germany. He obtained his PhD degree in Physics from University of Zurich, and his Master degree from ETH Zurich in Switzerland, and his bachelor degree in Aerospace Engineering at Harbin Institute of Technology in China. His research primarily focuses on theoretical particle physics, and he published various papers on Journal of High Energy Physics. He is also interested in cosmology and astrophysics that are closed related to space science.

Submission Instructions

Please select "Autonomous Safe Learning of Space Intelligent Systems" as the section/category during the submission process and indicate in your cover letter that your submission is intended for inclusion in the special issue.

Submission Deadline: August 30, 2023

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