2024 IEEE World Congress on Computational IntelligenceSpecial Session on Computational Intelligence in Space and Aerospace

30 June - 5 July 2024 in Yokohama, Japan

IEEE WCCI 2024 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: International Joint Conference on Neural Networks (IJCNN), IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), and IEEE Congress on Evolutionary Computation (IEEE CEC).

The Special Session on Computational Intelligence in Space and Aerospace (CISA) is organised IEEE CIS Task Force in Emerging Technologies in Space and Aerospace, and has been running since 2007. 

The session collects the 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.

Scope and Motivation

In an expanding world with limited resources and increasing complexity, optimisation and computational intelligence become a necessity. Optimisation can turn a problem into a solution and computational intelligence can offer new solutions to effectively make complexity manageable.

This special session collects the many diverse research of CI to space and aerospace problems.

All this is particularly true in space and aerospace where complex systems need to operate optimally often in harsh and inhospitable environment with high level of reliability.  In Space and Aerospace Sciences, many applications require the solution of global single and/or multi-objective optimization problems, including mixed variables, multi-modal and non-differentiable quantities. From global trajectory optimization to multidisciplinary aircraft and spacecraft design, from planning and scheduling for autonomous vehicles to the synthesis of robust controllers for airplanes or satellites, computational intelligence (CI) techniques have become an important – and in many cases inevitable – tool for tackling these kinds of problems, providing useful and non-intuitive solutions. Not only have Aerospace Sciences paved the way for the ubiquitous application of computational intelligence, but moreover, they have also led to the development of new approaches and methods.

In the last two decades, evolutionary computing, fuzzy logic, bio-inspired computing, artificial neural networks, swarm intelligence and other computational intelligence techniques have been used to find optimal trajectories, design optimal constellations or formations, evolve hardware, design robust and optimal aerospace systems (e.g. reusable launch vehicles, re-entry vehicles, etc.), evolve scheduled plans for unmanned aerial vehicles, improve aerodynamic design (e.g. airfoil and vehicle shape), optimize structures, improve the control of aerospace vehicles, regulate air traffic, etc. 

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

Authors are invited to submit papers on one or more of the following topics:

  • AI and Machine Learning for Space 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 on 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 Safety and Sustainability
  • Intelligent interfaces for human-machine interaction
  • Knowledge Discovery, Data Mining and presentation of large data sets

Yokohama is a city that inspires academic fusion and multidisciplinary & industrial association, the area boasts a number of universities, institutes and companies of advanced information technology.

IEEE Computational Intelligence Society