Computational Intelligence in Space and Aerospace

IEEE WCCI 2022 is the world’s largest technical event on computational intelligence, featuring the three flagship conferences of the IEEE Computational Intelligence Society (CIS) under one roof: the 2022 International Joint Conference on Neural Networks (IJCNN 2020), the 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2020), and the 2022 IEEE Congress on Evolutionary Computation (IEEE CEC 2020).

The Special Session on Computational Intelligence in Space and Aerospace collects many, diverse efforts made in the application of computational intelligence techniques, or related methods, to space and aerospace science and engineering. The session seeks to bring together researchers from around the globe for a stimulating discussion on recent advances in evolutionary methods for the solution of space and aerospace problems.

In particular computational intelligence methods specifically devised, adapted or tailored to address problems in space and aerospace applications or computational intelligence methods that were demonstrated to be particularly effective at solving space and aerospace related problems are welcome.

Topics

The session will cover, but is not limited to, the following topics:

• AI and Machine Learning for space and aerospace applications
• Global trajectory optimization
• Multidisciplinary design for space missions
• Formation and constellation design and control
• Optimal control of spacecraft and rovers
• Planning and scheduling for autonomous systems in space
• Multiobjective optimization for space applications
• Resource allocation and programmatics
• Evolutionary computation for Concurrent Engineering
• Distributed global optimization
• Mission planning and control
• Robust Mission Design under Uncertainties
• Intelligent search and optimization methods in aerospace applications
• Image analysis for Guidance Navigation and Control
• Autonomous exploration of interplanetary and planetary environments
• Implications of emerging AI fields such as Artificial Life or Swarm Intelligence in future space research
• Intelligent algorithms for fault identification, diagnosis and repair
• Intelligent control for aerospace systems
• Multi-agent systems approach and bio-inspired solutions for system design and control
• Autonomous vehicles and autonomous air traffic management
• AI for Space Traffic Management and Operations
• Intelligent interfaces for human-machine interaction
• Knowledge Discovery, Data Mining and presentation of large data sets
• Natural Language Processing for design and operation assistants

The submission deadline for papers is 31 January 2022. The papers will go through a double-blind review process, thus the papers should not reveal author’s identities.
Each paper is limited to 8 pages, including figures, tables, and references. All papers must be submitted through the IEEE WCCI 2022 online submission system. For special session papers, please select the respective special session title under the list of research topics in the submission system.

Chairs

Prof Massimiliano Vasile, University of Strathclyde

Prof Vasile is a Professor of Space Systems Engineering and Director of the Aerospace Centre of Excellence (ACE) at the University of Strathclyde. He is also chairman of the CIS task force on Computational Intelligence in Aerospace Sciences. From 2001-2003, he worked in the European Space Agency Advanced Concepts Team and introduced the research stream on global trajectory optimisation. His research interests include Astrodynamics, Space Systems Engineering, Computational Intelligence, Optimization Under Uncertainty exploring the limits of computer science at solving highly complex problems in science and engineering. He pioneered the use of evolutionary computation for the single and multi-objective global optimisation of space trajectories, and the combination of optimisation and imprecise probabilities to mitigate the effect of uncertainty in decision making and autonomous planning. More recently he has developed effective techniques for space safety and space environment management using artificial intelligence and machine learning. Prof Vasile is leading Stardust-R, a EU-funded international research network, where computational intelligence is applied to active debris removal and asteroid manipulation. He previously led UTOPIAE, a EU research network on optimisation and uncertainty treatment in aerospace engineering where advanced computational intelligence techniques were developed to deal with uncertainty in aerospace systems.

Prof David Camacho, Universidad Politécnica de Madrid

Prof David Camacho is a full professor at Computer Systems Engineering Department of Universidad Politécnica de Madrid (UPM), and the head of the Applied Intelligence and Data Analysis research group (AIDA) at UPM. He holds a Ph.D. in Computer Science from Universidad Carlos III de Madrid in 2001 with honours (best thesis award in Computer Science). His research interests include: Machine Learning (Clustering/Deep Learning), Computational Intelligence (Evolutionary Computation, Swarm Intelligence), Social Network Analysis, Fake News and Disinformation Analysis. He has participated/led more than 50 research projects (National and European: H2020, DG Justice, ISFP, and Erasmus+), related to the design and application of artificial intelligence methods for data mining and optimization for problems emerging in industrial scenarios (coal mining, steel), aeronautics, aerospace engineering, cybercrime/cyber intelligence, social networks applications, or video games among others. He is an Associate Editor of several journals, including Information Fusion, Ambient Intelligence & Humanized Computing, Expert Systems, and Cognitive Computation.

Dr Victor Rodriguez-Fernandez, Universidad Politécnica de Madrid

Dr Victor Rodriguez-Fernandez is an assistant professor in the school of computer systems engineering of Universidad Politécnica de Madrid (UPM). He holds a PhD in computer science at the Autonomous University of Madrid. Currently he is part of the Applied Intelligence and Data Analysis (AIDA) research group at UPM, where he is involved with several projects funded by the European Commission. His research interests revolve around practical applications of deep learning, with a special emphasis on the domains of industry and space.

Prof Domenico Quagliarella, CIRA

Prof Domenico Quagliarella received in May 1988 the MS degree and in July 1993 the Ph.D. in Aerospace Engineering from the University “Federico II” in Naples, Italy. In July 1988, he got a research engineer position at CIRA, the Italian Aerospace Research Centre, where he is currently Head of the Multidisciplinary Analysis and Design Group of Fluid Mechanics Department. His research interests are the application of hybrid multi-objective optimization methods to aerodynamic and multidisciplinary design, the use of approximate fitness evaluators for efficiency improvement in optimization, and uncertainty quantification for robust and reliability-based design. He is the author of about 90 international journal and conference papers. He is also editor of five books and two special issues of academic journals.