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Swarm Robotics, From Biology to Robotics
Swarm Robotics, From Biology to Robotics
Edited by
Ester Martínez Martín
In-Tech
intechweb.org
Published by In-Teh In-Teh Olajnica 19/2, 32000 Vukovar, Croatia Abstracting and non-profit use of the material is permitted with credit to the source. Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published articles. Publisher assumes no responsibility liability for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained inside. After this work has been published by the In-Teh, authors have the right to republish it, in whole or part, in any publication of which they are an author or editor, and the make other personal use of the work. © 2010 In-teh www.intechweb.org Additional copies can be obtained from:
[email protected] First published March 2010 Printed in India Technical Editor: Maja Jakobovic Cover designed by Dino Smrekar Swarm Robotics, From Biology to Robotics, Edited by Ester Martínez Martín p. cm. ISBN 978-953-307-075-9
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Preface In nature, it is possible to observe a cooperative behaviour in all animals, since, according to Charles Darwin’s theory, every being, from ants to human beings, form groups in which most individuals work for the common good. However, although study of dozens of social species has been done for a century, details of how and why cooperation evolved remain to be worked out. Actually, cooperative behaviour has been studied from different points of view. For instance evolutionary biologists and animal behaviour researchers look for the genetic basis and molecular drivers of this kind of behaviours, as well as the physiological, environmental, and behavioural impetus for sociality; while neuroscientists discover key correlations between brain chemicals and social strategies. From a more mathematical point of view, economics have developed a modelling approach, based on game theory, to quantify cooperation and predict behavioural outcomes under different circumstances. Although game theory has helped to reveal an apparently innate desire for fairness, developed models are still imperfect. Furthermore, social insect behaviour, from a biological point of view, might be emulated by a micro-robot colony and, in that way, analysis of a tremendous amount of insect trajectories and manual event counting is replaced by tracking several miniature robots on a desktop table. Swarm robotics is a new approach that emerged on the field of artificial swarm intelligence, as well as the biological studies of insects (i.e. ants and other fields in nature) which coordinate their actions to accomplish tasks that are beyond the capabilities of a single individual. In particular, swarm robotics is focused on the coordination of decentralised, self-organised multi-robot systems in order to describe such a collective behaviour as a consequence of local interactions with one another and with their environment. Research in swarm robotics involves from robot design to their controlling behaviours, by including tracking techniques for systematically studying swarm-behaviour. Moreover, swarm robotic-based techniques can be used in a number of applications. This is, for instance, the case of the Particle Swarm Optimization (PSO) which is a direct search method, based on swarm concepts, that models and predicts social behaviour in the presence of objectives. In this case, the swarm under study is typically modelled by particles in multidimensional space that h