Cryogenic Computing and Space Applications

The field of space computing is moving towards the development of highly efficient and robust systems capable of operating in extremely cold environments. Researchers are exploring the use of Field Programmable Gate Arrays (FPGAs) and neural networks to enhance onboard computing systems. Innovative control techniques, such as Genetic Fuzzy Trees and adaptive control approaches, are being developed to improve the efficiency and safety of robotic systems and spacecraft. These advances have the potential to enable autonomous operations, improve satellite maintenance, and enhance the overall performance of space missions. Noteworthy papers include:

  • A paper demonstrating the operation of FPGAs at extremely low temperatures, with improved jitter performance and reduced LUT delays.
  • A study presenting a Genetic Fuzzy-Enabled Framework for robotic manipulation, which showed an 18.5% improvement in performance compared to traditional control schemes.

Sources

Implementation of Field Programmable Gate Arrays (FPGAs) in Extremely Cold Environments for Space and Cryogenic Computing Applications

A Genetic Fuzzy-Enabled Framework on Robotic Manipulation for In-Space Servicing

Monocular inspection of spacecraft under illumination constraints and avoidance regions

FPGA-Based Neural Network Accelerators for Space Applications: A Survey

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