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Reconfigurable On-Board Vision Processing for Small Autonomous Vehicles

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Abstract

This paper addresses the challenge of supporting real-time vision processing on-board small autonomous vehicles. Local vision gives increased autonomous capability, but it requires substantial computing power that is difficult to provide given the severe constraints of small size and battery-powered operation. We describe a custom FPGA-based circuit board designed to support research in the development of algorithms for image-directed navigation and control. We show that the FPGA approach supports real-time vision algorithms by describing the implementation of an algorithm to construct a three-dimensional (3D) map of the environment surrounding a small mobile robot. We show that FPGAs are well suited for systems that must be flexible and deliver high levels of performance, especially in embedded settings where space and power are significant concerns.

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Author information

Correspondence to Wade S Fife.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Keywords

  • Mobile Robot
  • Control Structure
  • Computing Power
  • Vision Processing
  • Circuit Board