A Survey of autonomous vision-based See and Avoid for Unmanned Aircraft Systems


Autoria(s): Mcfadyen, Aaron; Mejias, Luis
Data(s)

01/01/2016

Resumo

This paper provides a comprehensive review of the vision-based See and Avoid problem for unmanned aircraft. The unique problem environment and associated constraints are detailed, followed by an in-depth analysis of visual sensing limitations. In light of such detection and estimation constraints, relevant human, aircraft and robot collision avoidance concepts are then compared from a decision and control perspective. Remarks on system evaluation and certification are also included to provide a holistic review approach. The intention of this work is to clarify common misconceptions, realistically bound feasible design expectations and offer new research directions. It is hoped that this paper will help us to unify design efforts across the aerospace and robotics communities.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/90842/

Publicador

Elsevier

Relação

http://eprints.qut.edu.au/90842/1/aeroprog2015.pdf

http://www.sciencedirect.com/science/article/pii/S0376042115300208

DOI:http://dx.doi.org/10.1016/j.paerosci.2015.10.002

Mcfadyen, Aaron & Mejias, Luis (2016) A Survey of autonomous vision-based See and Avoid for Unmanned Aircraft Systems. Progress in Aerospace Sciences, 80, pp. 1-17.

Direitos

Copyright 2015 Elsevier

This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

Fonte

Australian Research Centre for Aerospace Automation; School of Electrical Engineering & Computer Science; Science & Engineering Faculty

Palavras-Chave #080104 Computer Vision #090100 AEROSPACE ENGINEERING #Detect and Avoid #Unmanned Aircraft Systems #Collision avoidance #See and Avoid #Visual control
Tipo

Journal Article