How to Choose the Best Embedded Processing Platform for on-Board UAV Image Processing ?

Abstract

For a variety of tasks, complex image processing algorithms are a necessity to make UAVs more autonomous. Often, the processing of images of the on-board camera is performed on a ground station, which severely limits the operating range of the UAV. Often, offline processing is used since it is difficult to find a suitable hardware platform to run a specific vision algorithm on-board the UAV. First of all, it is very hard to find a good trade-off between speed, power consumption and weight of a specific hardware platform and secondly, due to the variety of hardware platforms, it is difficult to find a suitable hardware platform and to estimate the speed the user’s algorithm will run on that hardware platform. In this paper we tackle those problems by presenting a framework that automatically determines the most-suited hardware platform for each arbitrary complex vision algorithm. Additionally, our framework estimates the speed, power consumption and flight time of this algorithm for a variety of hardware platforms on a specific UAV. We demonstrate this methodology on two real-life cases and give an overview of the present top processing CPU-based platforms for on-board UAV image processing.