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Authors: Benjamin N. Passow 1 and Mario Gongora 2

Affiliations: 1 Institute of Creative Technologies, De Montfort University, United Kingdom ; 2 Centre for Computational Intelligence, De Montfort University, United Kingdom

Keyword(s): Genetic algorithm, robot, helicopter, PID, control.

Related Ontology Subjects/Areas/Topics: Evolutionary Computation and Control ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Robot Design, Development and Control ; Robotics and Automation

Abstract: This work presents the optimisation of the heading controller of a small flying robot. A genetic algorithm (GA) has been used to tune the proportional, integral, and derivative (PID) parameters of the helicopter’s controller. Instead of evaluating each individual’s fitness in an artificial simulation, the actual flying robot has been used. The performance of a hand-tuned PID controller is compared to the GA-tuned controller. Tests on the helicopter confirm that the GA’s solutions result in a better controller performance. Further more, results suggest that evaluating the GA’s individuals on the real flying robot increases the controller’s robustness.

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Paper citation in several formats:
N. Passow, B. and Gongora, M. (2008). OPTIMISING A FLYING ROBOT - Controller Optimisation using a Genetic Algorithm on a Real-World Robot. In Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO; ISBN 978-989-8111-31-9; ISSN 2184-2809, SciTePress, pages 151-156. DOI: 10.5220/0001496901510156

@conference{icinco08,
author={Benjamin {N. Passow}. and Mario Gongora.},
title={OPTIMISING A FLYING ROBOT - Controller Optimisation using a Genetic Algorithm on a Real-World Robot},
booktitle={Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO},
year={2008},
pages={151-156},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001496901510156},
isbn={978-989-8111-31-9},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO
TI - OPTIMISING A FLYING ROBOT - Controller Optimisation using a Genetic Algorithm on a Real-World Robot
SN - 978-989-8111-31-9
IS - 2184-2809
AU - N. Passow, B.
AU - Gongora, M.
PY - 2008
SP - 151
EP - 156
DO - 10.5220/0001496901510156
PB - SciTePress