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Aerospace 2016, 3(3), 21; doi:10.3390/aerospace3030021

Bio-Inspired Principles Applied to the Guidance, Navigation and Control of UAS

1
The Queensland Brain Institute, The University of Queensland, Brisbane 4072, Australia
2
The School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane 4072, Australia
3
Autonomous Systems Program, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Pullenvale 4069, Australia
*
Author to whom correspondence should be addressed.
Academic Editor: Javaan Chahl
Received: 28 April 2016 / Revised: 25 June 2016 / Accepted: 6 July 2016 / Published: 20 July 2016
(This article belongs to the Collection Unmanned Aerial Systems)

Abstract

This review describes a number of biologically inspired principles that have been applied to the visual guidance, navigation and control of Unmanned Aerial System (UAS). The current limitations of UAS systems are outlined, such as the over-reliance on GPS, the requirement for more self-reliant systems and the need for UAS to have a greater understanding of their environment. It is evident that insects, even with their small brains and limited intelligence, have overcome many of the shortcomings of the current state of the art in autonomous aerial guidance. This has motivated research into bio-inspired systems and algorithms, specifically vision-based navigation, situational awareness and guidance. View Full-Text
Keywords: situational awareness; optic flow; visual odometry; snapshot-based navigation; pursuit; interception; constant bearing situational awareness; optic flow; visual odometry; snapshot-based navigation; pursuit; interception; constant bearing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Strydom, R.; Denuelle, A.; Srinivasan, M.V. Bio-Inspired Principles Applied to the Guidance, Navigation and Control of UAS. Aerospace 2016, 3, 21.

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