Cross-entropy optimization for scaling factors of a fuzzy controller : a see-and-avoid approach for unmanned aerial systems

Olivares-Mendez, Miguel A., Mejias, Luis, Campoy, Pascual, & Mellado-Bataller, Ignacio (2013) Cross-entropy optimization for scaling factors of a fuzzy controller : a see-and-avoid approach for unmanned aerial systems. Journal of Intelligent & Robotic Systems, 69(1-4), pp. 189-205.

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Abstract

The Cross-Entropy (CE) is an efficient method for the estimation of rare-event probabilities and combinatorial optimization. This work presents a novel approach of the CE for optimization of a Soft-Computing controller. A Fuzzy controller was designed to command an unmanned aerial system (UAS) for avoiding collision task. The only sensor used to accomplish this task was a forward camera. The CE is used to reach a near-optimal controller by modifying the scaling factors of the controller inputs. The optimization was realized using the ROS-Gazebo simulation system. In order to evaluate the optimization a big amount of tests were carried out with a real quadcopter.

Impact and interest:

9 citations in Scopus
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8 citations in Web of Science®

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220 since deposited on 16 Jan 2013
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ID Code: 56454
Item Type: Journal Article
Refereed: Yes
Keywords: UAV; UAS; Fuzzy logic; Fuzzy control; Cross-Entropy; Visual servoing; Computer vision; Sense and avoid; See and avoid; Optimization
DOI: 10.1007/s10846-012-9791-5
ISSN: 1573-0409
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Aircraft Performance and Flight Control Systems (090104)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Control Systems Robotics and Automation (090602)
Divisions: Current > Research Centres > Australian Research Centre for Aerospace Automation
Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 Springer Netherlands
Deposited On: 16 Jan 2013 00:58
Last Modified: 30 Jan 2013 00:19

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