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Embedded Computation Architectures for Autonomy in Unmanned Aircraft Systems (UAS).

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Summary
This summary is machine-generated.

Future autonomous Unmanned Aircraft Systems (UAS) demand advanced embedded computing. Current architectures are insufficient, necessitating dynamically reconfigurable hardware for enhanced performance and energy efficiency in UAS design.

Keywords:
UASUAS applicationsautonomycomputing architectures

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Area of Science:

  • Aerospace Engineering
  • Computer Engineering
  • Robotics

Background:

  • Future Unmanned Aircraft Systems (UAS) require significant onboard computing power for increased autonomy.
  • Existing embedded systems face challenges in meeting these escalating computational demands.

Purpose of the Study:

  • To analyze the computational resource requirements for future autonomous UAS.
  • To propose a framework for classifying UAS tasks and defining autonomy levels.
  • To investigate the implications of autonomy on embedded system design.

Main Methods:

  • Classification of common UAS tasks (flight, navigation, safety, mission) and executing entities.
  • Analysis of task combinations to define autonomy levels.
  • Review of current state-of-the-art hardware and software for UAS tasks.

Main Results:

  • Established a link between UAS applications, required tasks, autonomy levels, and computing resource needs.
  • Identified that current computing architectures are inadequate for future UAS autonomy.
  • Highlighted the potential of dynamically reconfigurable hardware for improved performance and energy efficiency.

Conclusions:

  • Future autonomous UAS necessitate a re-evaluation of embedded system design.
  • Dynamically reconfigurable hardware presents a promising solution for meeting future computational demands.
  • The embedded system should be considered a critical component in UAS development.