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Authors: Zenon Hendzel ; Marcin Szuster and Andrzej Burghardt

Affiliation: Rzeszow University of Technology, Poland

Keyword(s): Behavioural Control, Adaptive Critic Design, Robots Formation, Reactive Navigation, Neural Networks.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Biomedical Signal Processing ; Complex Artificial Neural Network Based Systems and Dynamics ; Computational Intelligence ; Enterprise Information Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neural Network Software and Applications ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: The article presents a hierarchical control system build using artificial intelligence methods, that generates a trajectory of the wheeled mobile robots formation, and realises the tracking control task of all agents. The hierarchical control system consists of a navigator, based on a conception of behavioural control signals coordination, and individual tracking control systems for all mobile robots in the formation. The navigator realises a sensor-based approach to the path planning process in the unknown 2-D environment with static obstacles. The navigator presents a new approach to the behavioural control, where one Neural dynamic programming algorithm generates the control signal for the complex behaviour, which is a composition of two individual behaviours: “goal-seeking”and “obstacle avoiding”. Influence of individual behaviours on the navigator control signal depends on the environment conditions and changes fluently. On the basis of control signal generated by the navigator are computed the desired collision-free trajectories for all robots in formation, realised by the tracking control systems. Realisation of generated trajectories guarantees reaching the goal by selected point of the robots formation with obstacles avoiding by all agents. Computer simulations have been conducted to illustrate the process of path planning in the different environment conditions. (More)

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Paper citation in several formats:
Hendzel, Z.; Szuster, M. and Burghardt, A. (2012). Artificial Intelligence Methods in Reactive Navigation of Mobile Robots Formation. In Proceedings of the 4th International Joint Conference on Computational Intelligence (IJCCI 2012) - NCTA; ISBN 978-989-8565-33-4; ISSN 2184-3236, SciTePress, pages 466-473. DOI: 10.5220/0004113404660473

@conference{ncta12,
author={Zenon Hendzel. and Marcin Szuster. and Andrzej Burghardt.},
title={Artificial Intelligence Methods in Reactive Navigation of Mobile Robots Formation},
booktitle={Proceedings of the 4th International Joint Conference on Computational Intelligence (IJCCI 2012) - NCTA},
year={2012},
pages={466-473},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004113404660473},
isbn={978-989-8565-33-4},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 4th International Joint Conference on Computational Intelligence (IJCCI 2012) - NCTA
TI - Artificial Intelligence Methods in Reactive Navigation of Mobile Robots Formation
SN - 978-989-8565-33-4
IS - 2184-3236
AU - Hendzel, Z.
AU - Szuster, M.
AU - Burghardt, A.
PY - 2012
SP - 466
EP - 473
DO - 10.5220/0004113404660473
PB - SciTePress