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Choosing the Best Embedded Processing Platform for On-Board UAV Image Processing

  • Dries HulensEmail author
  • Jon Verbeke
  • Toon Goedemé
Part of the Communications in Computer and Information Science book series (CCIS, volume 598)

Abstract

Nowadays, complex image processing algorithms are a necessity to make UAVs more autonomous. Currently, the processing of images of the on-board camera is often performed on a ground station, thus severely limiting the operating range. On-board processing has numerous advantages, however determining a good trade-off between speed, power consumption and weight of a specific hardware platform for on-board processing is hard. Many hardware platforms exist, and finding the most suited one for a specific vision algorithm is difficult. We present a framework that automatically determines the most-suited hardware platform given an arbitrary complex vision algorithm. Our framework estimates the speed, power consumption and flight time of this algorithm for multiple hardware platforms on a specific UAV. We demonstrate this methodology on two real-life cases and give an overview of the present top performing CPU-based platforms for on-board UAV image processing.

Keywords

UAV Vision On-board Real-time Speed estimation Power estimation Flight time estimation 

Notes

Acknowledgements

This work is funded by KU Leuven via the CAMETRON project.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.EAVISEKU LeuvenLeuvenBelgium
  2. 2.Department of EngineeringKU LeuvenLeuvenBelgium

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