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Authors: Thomas Statheros 1 ; Gareth Howells 1 ; Pierre Lorrentz 1 and Klaus McDonald-Maier 2

Affiliations: 1 University of Kent, United Kingdom ; 2 University of Essex, United Kingdom

Keyword(s): Autonomous Intelligent Guidance, Potential Field Algorithms, Weightless Neural Systems.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Computational Intelligence ; Enterprise Information Systems ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Machine Learning in Control Applications ; Neural Networks Based Control Systems ; Robotics and Automation ; Soft Computing ; Vehicle Control Applications

Abstract: The ACOS project seeks to improve and develop novel robot guidance and control systems integrating Novel Potential Field autonomous navigation techniques, multi-classifier design with direct hardware implementation. The project development brings together a number of complementary technologies to form an overall enhanced system. The work is aimed at guidance and collision avoidance control systems for applications in air, land and water based vehicles for passengers and freight. Specifically, the paper addresses the generic nature of the previously presented novel Potential Field Algorithm based on the combination of the associated rule based mathematical algorithm and the concept of potential field. The generic nature of the algorithm allows it to be efficient, not only when applied to multi-autonomous robots, but also when applied to collision avoidance between a single autonomous agent and an obstacle displaying random velocity. In addition, the mathematical complexity, which is i nherent when a large number of autonomous vehicles and dynamic obstacles are present, is reduced via the incorporation of an intelligent weightless multi-classifier system which is also presented. (More)

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Paper citation in several formats:
Statheros, T.; Howells, G.; Lorrentz, P. and McDonald-Maier, K. (2009). A NOVEL POTENTIAL FIELD ALGORITHM AND AN INTELLIGENT MULTI-CLASSIFIER FOR THE AUTOMATED CONTROL AND GUIDANCE SYSTEM (ACOS). In Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO, ISBN 978-989-8111-99-9; ISSN 2184-2809, pages 337-342. DOI: 10.5220/0002171203370342

@conference{icinco09,
author={Thomas Statheros. and Gareth Howells. and Pierre Lorrentz. and Klaus McDonald{-}Maier.},
title={A NOVEL POTENTIAL FIELD ALGORITHM AND AN INTELLIGENT MULTI-CLASSIFIER FOR THE AUTOMATED CONTROL AND GUIDANCE SYSTEM (ACOS)},
booktitle={Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,},
year={2009},
pages={337-342},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002171203370342},
isbn={978-989-8111-99-9},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,
TI - A NOVEL POTENTIAL FIELD ALGORITHM AND AN INTELLIGENT MULTI-CLASSIFIER FOR THE AUTOMATED CONTROL AND GUIDANCE SYSTEM (ACOS)
SN - 978-989-8111-99-9
IS - 2184-2809
AU - Statheros, T.
AU - Howells, G.
AU - Lorrentz, P.
AU - McDonald-Maier, K.
PY - 2009
SP - 337
EP - 342
DO - 10.5220/0002171203370342