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2018 | Buch

Introduction to Swarm Robotics Kapitel lesen Erstes Kapitel lesen

Swarm Robotics: A Formal Approach

verfasst von: Prof. Dr. Heiko Hamann

Verlag: Springer International Publishing

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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SUCHEN

Über dieses Buch

This book provides an introduction to Swarm Robotics, which is the application of methods from swarm intelligence to robotics. It goes on to present methods that allow readers to understand how to design large-scale robot systems by going through many example scenarios on topics such as aggregation, coordinated motion (flocking), task allocation, self-assembly, collective construction, and environmental monitoring. The author explains the methodology behind building multiple, simple robots and how the complexity emerges from the multiple interactions between these robots such that they are able to solve difficult tasks. The book can be used as a short textbook for specialized courses or as an introduction to Swarm Robotics for graduate students, researchers, and professionals who want a concise introduction to the field.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Introduction to Swarm Robotics
Abstract
We introduce fundamental concepts of swarm robotics and get a little overview.Swarm robotics is a complex approach that requires an understanding of how to define swarm behavior, whether there is a minimum size of swarms, what are the requirements and properties of swarm systems. We define self-organization and develop an understanding of feedback systems. Swarms do not necessarily need to be homogeneous but can consist of different types of robots making them heterogeneous. We also discus the interaction of robot swarms with human beings as a factor.
Heiko Hamann
Chapter 2. Short Introduction to Robotics
Abstract
This is a little crash course in robotics for the case you haven’t heard so much about robotics yet.This short introduction to mobile robotics is starting from a general perspective and quickly introduces fundamental concepts, such as sensors, actuators, and kinematics. We continue with a short introduction to open-loop and closed-loop control. Agent models, behavior-based robotics, and potential field control are introduced as control options particularly interesting for swarm robots. We conclude with a presentation of several hardware platforms dedicated to swarm robotics, such as the s-bot, the I-SWARM robot, Alice, and the Kilobot among others.
Heiko Hamann
Chapter 3. Short Journey Through Nearly Everything
Abstract
We do a little example tour through many methods and ideas we are going to study in this book.This is a quick walk through the methodology that is of interest to design swarm robot systems. We model a robot controller with a finite state machine for a collective-decision-making problem. We immediately face the typical challenge of distinguishing between microscopic information that is available to an individual robot and macroscopic information that is only available to an external observer. We continue with a simple macroscopic model of collective-decision making and discuss whether it represents a self-organizing system.
Heiko Hamann
Chapter 4. Scenarios of Swarm Robotics
Abstract
We do an extensive check of what typical scenarios of swarm robotics have been investigated and what methods have been published.This is an extensive guide through the literature on swarm robotics. It is structured by the investigated scenarios and starts from tasks of low complexity, such as aggregation and dispersion. A discussion of pattern formation, object clustering, sorting, and self-assembly follows. Collective construction is already a rather complex scenario that combines several subtasks, such as collective decision-making and collective transport. We take the example of collective manipulation to discuss the interesting phenomenon of super-linear performance increase. Not only the swarm performance increases with increasing swarm size but even the individual robot’s efficiency. Flocking, collective motion, foraging, and shepherding are discussed as typical examples of swarm behaviors. Bio-hybrid systems as combinations of robots and living organisms are quickly introduced. We conclude with a discussion of what could arguably be called “swarm robotics 2.0”—a few recent very promising approaches, such as error detection, security, swarms as interfaces, and swarm robotics as field robotics.
Heiko Hamann
Chapter 5. Modeling Swarm Systems and Formal Design Methods
Abstract
We learn about why and how we model systems of swarm robotics and how sophisticated design methods can look like.Modeling is motivated and introduced as a dimension reduction technique for swarm robotics. Then we start from a discussion of local sampling, which is the challenge in swarm robotics of dealing with local information. The local samples are not representative for the whole swarm and hence we require a methodology to work with unreliable local information. Several modeling techniques are introduced that are frequently applied in swarm robotics, such as rate equations and spatial models based on ordinary and partial differential equations. We also discuss network models and the interesting option of using robot swarms as models for biology.
In the second part, we turn to formal design approaches starting from multi-scale modeling. Software engineering approaches and verification techniques are discussed and we look into the so-called concept of global-to-local programming.
Heiko Hamann
Chapter 6. Collective Decision-Making
Abstract
We study methods of collective decision-making—an important capability for a swarm to become autonomous.
Collective decision-making is an essential skill for a swarm of robots in order to form an autonomous system also on the macroscopic level. We start with traditional methods to describe decision-making and rational agents. Group decision-making is introduced and we investigate the example of collective motion as a decision-making process. It follows an extensive walk through modeling techniques for collective decision-making, such as urn models, voter model, majority rule, Hegselmann–Krause model, Kuramoto model, Ising model, fiber bundle model, and sociophysics by Serge Galam among other approaches. We conclude with a discussion of hardware implementations of collective decision-making in swarm robotics.
Heiko Hamann
Chapter 7. Case Study: Adaptive Aggregation
Abstract
We try the impossible and summarize almost all we have learned about in this book.In this little case study we try to integrate all different techniques that one requires to design a system of swarm robots. The task is rather simple and we focus on adaptive aggregation, that is, the swarm has to aggregate at a particular spot determined by environmental features. We follow a biological role model and apply standard modeling techniques of swarm robotics. Finally, the control algorithm and the micro-macro model are verified against robot experiments.
Heiko Hamann
Backmatter
Metadaten
Titel
Swarm Robotics: A Formal Approach
verfasst von
Prof. Dr. Heiko Hamann
Copyright-Jahr
2018
Electronic ISBN
978-3-319-74528-2
Print ISBN
978-3-319-74526-8
DOI
https://doi.org/10.1007/978-3-319-74528-2

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