Aircraft collision avoidance using spherical visual predictive control and single point features


Autoria(s): Mcfadyen, Aaron; Mejias, Luis; Corke, Peter; Pradalier, Cedric
Contribuinte(s)

Amato, Nancy

Data(s)

05/11/2013

Resumo

This paper presents practical vision-based collision avoidance for objects approximating a single point feature. Using a spherical camera model, a visual predictive control scheme guides the aircraft around the object along a conical spiral trajectory. Visibility, state and control constraints are considered explicitly in the controller design by combining image and vehicle dynamics in the process model, and solving the nonlinear optimization problem over the resulting state space. Importantly, range is not required. Instead, the principles of conical spiral motion are used to design an objective function that simultaneously guides the aircraft along the avoidance trajectory, whilst providing an indication of the appropriate point to stop the spiral behaviour. Our approach is aimed at providing a potential solution to the See and Avoid problem for unmanned aircraft and is demonstrated through a series.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/61552/

Publicador

IEEE

Relação

http://eprints.qut.edu.au/61552/1/IROS_2013_MMCP10.pdf

DOI:10.1109/IROS.2013.6696331

Mcfadyen, Aaron, Mejias, Luis, Corke, Peter, & Pradalier, Cedric (2013) Aircraft collision avoidance using spherical visual predictive control and single point features. In Amato, Nancy (Ed.) Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Tokyo Big Sight, Tokyo, pp. 50-46.

Direitos

Copyright 2013 IEEE

This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

Fonte

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

Palavras-Chave #080100 ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING #080104 Computer Vision #090100 AEROSPACE ENGINEERING #090104 Aircraft Performance and Flight Control Systems #090602 Control Systems Robotics and Automation #aircraft control #autonomous aerial vehicles #collision avoidance #control system synthesis #nonlinear control systems #optimisation #predictive control #robot vision
Tipo

Conference Paper