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Authors: Eniko T. Enikov 1 and Juan-Antonio Escareno 2

Affiliations: 1 University of Arizona, United States ; 2 Institut Polytechnique des Sciences Avancées (IPSA), France

ISBN: 978-989-758-122-9

Keyword(s): Micro-Air Vehicles, Artificial Neural Network, Path Planning, Body Schema, Cognitive Robotics.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Cognitive Robotics ; Control and Supervision Systems ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Neural Networks Based Control Systems ; Perception and Awareness ; Robot Design, Development and Control ; Robotics and Automation

Abstract: To date, most autonomous micro air vehicles (MAV-s) operate in a controlled environment, where the location of and attitude of the aircraft are measured be dedicated high-power computers with IR tracking capability. If MAV-s are to ever exit the lab and carry out autonomous missions, their flight control systems needs to utilize on-board sensors and high-efficiency attitude determination algorithms. To address this need, we investigate the feasibility of using body schemas to carry out path planning in the vision space of the MAV. Body schemas are a biologically-inspired approach, emulating the plasticity of the animal brains, allowing efficient representation of non-linear mapping between the body configuration space, i.e. its generalized coordinates and the resulting sensory outputs. This paper presents a numerical experiment of generating landing trajectories of a miniature rotor-craft using the notion of body and image schemas. More specifically, we demonstrate how a traj ectory planning can be executed in the image space using a pseudo-potential functions and a gradient-based maximum seeking algorithm. It is demonstrated that a neural-gas type neural network, trained through Hebbian-type learning algorithm can learn a mapping between the rotor-craft position/attitude and the output of its vision sensors. Numerical simulations of the landing performance of a physical model is also presented, The resulting trajectory tracking errors are less than 8 %. (More)

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Paper citation in several formats:
Enikov, E. and Escareno, J. (2015). Application of Sensory Body Schemas to Path Planning for Micro Air Vehicles (MAVs).In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-122-9, pages 25-31. DOI: 10.5220/0005547000250031

@conference{icinco15,
author={Eniko T. Enikov. and Juan{-}Antonio Escareno.},
title={Application of Sensory Body Schemas to Path Planning for Micro Air Vehicles (MAVs)},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2015},
pages={25-31},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005547000250031},
isbn={978-989-758-122-9},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Application of Sensory Body Schemas to Path Planning for Micro Air Vehicles (MAVs)
SN - 978-989-758-122-9
AU - Enikov, E.
AU - Escareno, J.
PY - 2015
SP - 25
EP - 31
DO - 10.5220/0005547000250031

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