Biologically Inspired Collective Robotics

Biologically Inspired Collective Robotics

C. Ronald Kube (Syncrude Research Centre, Canada and University of Alberta, Canada), Chris A.C. Parker (University of Alberta, Canada), Tao Wang (University of Alberta, Canada) and Hong Zhang (University of Alberta, Canada)
Copyright: © 2005 |Pages: 31
DOI: 10.4018/978-1-59140-312-8.ch015
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Abstract

In this chapter, we review our recent research in the area of collective robotics, and the problem of controlling multiple robots in the completion of common tasks. Our approach is characterized with a strong inclination for biological inspiration in which examples in nature — social insects in particular — are used as a way of designing strategies for controlling robots. This approach has been successfully applied to the study of three representative tasks, namely, collective box-pushing, collective construction, and collective sorting. Collective box-pushing deals with the purposeful motion of an object too large to be moved by a single robot and we rely on the group prey transport phenomenon found in ants to derive the necessary behaviors for accomplishing this task. Collective construction is concerned with the building of a geometric structure with the combined efforts of many individuals in parallel, without centralized control and we study a species of ant known to possess this capability, to model and control the process of creating a circular nest with multiple robots. Finally, in collective sorting the broad behavior in ants serves as the motivation behind designing robotic behaviors that depend on only local sensing in clustering objects of different types into separate piles. The success of our proposed approach is supported by both simulation and physical experiments using robots.

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Table of Contents
Foreword
Moshe Sipper
Acknowledgments
Leandro Nunes de Castro, Fernando J. Von Zuben
Chapter 1
Leandro Nunes de Castro, Fernando J. Von Zuben
Biologically inspired computing is just one of the branches of natural computing, which also encompasses artificial life, fractal geometry and... Sample PDF
From Biologically Inspired Computing to Natural Computing
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Chapter 2
Penousal Machado, Francisco B. Pereira, Jorge Tavares, Ernesto Costa, Amílcar Cardoso
In this chapter we study the feasibility of using Turing Machines as a model for the evolution of computer programs. To assess this idea we select... Sample PDF
Evolutionary Turing Machines: The Quest for Busy Beavers
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Chapter 3
Fabiano Luis de Sousa, Fernando Manuel Ramos, Roberto Luiz Galski, Issamu Muraoka
In this chapter a recently proposed meta-heuristic devised to be used in complex optimization problems is presented. Called Generalized Extremal... Sample PDF
Generalized External Optimization: A New Meta-Heuristic Inspired by a Model of Natural Evolution
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Chapter 4
Taro Yabuki, Hitoshi Iba
In this chapter, a new representation scheme for Genetic Programming (GP) is proposed. We need a Turing-complete representation for a general method... Sample PDF
Genetic Programming Using a Turing-Complete Representation: Recurrent Network Consisting of Trees
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Chapter 5
Cândida Ferreira
In this chapter an artificial problem solver inspired in natural genotype/phenotype systems — gene expression programming — is presented. As an... Sample PDF
Gene Expression Programming and the Evolution of Computer Programs
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Chapter 6
Vincenzo Cutello, Giuseppe Nicosia
The chapter describes the theory of clonal selection and its usage in designing and implementing immunological algorithms for problem solving and... Sample PDF
The Clonal Selection Principle for In Silico and In Vitro Computing
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Chapter 7
Sergio Alonso, Oscar Cordon, Iñaki Fernández de Viana, Francisco Herrera
This chapter introduces two different ways to integrate Evolutionary Computation Components in Ant Colony Optimization (ACO) Meta-heuristic. First... Sample PDF
Integrating Evolutionary Computation Components in Ant Colony Optimization
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Chapter 8
Gurdip Singh, Sanjoy Das, Shekhar V. Gosavi, Sandeep Pujar
This chapter introduces ant colony optimization as a method for computing minimum Steiner trees in graphs. Tree computation is achieved when... Sample PDF
Ant Colony Algorithms for Steiner Trees: An Application to Routing in Sensor Networks
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Chapter 9
Vahid Sherafat, Leandro Nunes de Castro, Eduardo Raul Hruschka
Algorithms inspired by the collective behavior of social organisms, from insect colonies to human societies, promoted the emergence of a new field... Sample PDF
The Influence of Pheromone and Adaptive Vision in the Standard Ant Clustering Algorithm
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Chapter 10
James Kennedy
Particle swarm optimization is a computer paradigm that is based on human social influence and cognition. Candidate problem solutions are randomly... Sample PDF
Particle Swarms: Optimization Based on Sociocognition
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Chapter 11
Angelo Loula, Ricardo Gudwin, Sidarta Ribeiro, Ivan de Araujo, João Queiroz
Here we propose, based on the Peircean semiotics and informed by neuroethological constraints, a methodology to simulate the emergence of symbolic... Sample PDF
Synthetic Approach to Semiotic Artificial Creatures
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Chapter 12
Jean-Philippe Rennard
This chapter introduces the twin deadlocks of strong artificial life. Conceptualization of life is a deadlock both because of the existence of a... Sample PDF
Perspectives for Strong Artificial Life
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Chapter 13
Peter J. Bentley
Fractal proteins are a new evolvable method of mapping genotype to phenotype through a developmental process, where genes are expressed into... Sample PDF
Controlling Robots with Fractal Gene Regulatory Networks
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Chapter 14
Mark Neal, Jon Timmis
The field of biologically inspired computing has generated many novel, interesting and useful computational systems. None of these systems alone is... Sample PDF
Once More Unto the Breach: Towards Artificial Homeostasis
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Chapter 15
C. Ronald Kube, Chris A.C. Parker, Tao Wang, Hong Zhang
In this chapter, we review our recent research in the area of collective robotics, and the problem of controlling multiple robots in the completion... Sample PDF
Biologically Inspired Collective Robotics
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Chapter 16
Thomas P. Trappenberg
In this chapter a brief review is given of computational systems that are motivated by information processing in the brain, an area that is often... Sample PDF
Continuous Attractor Neural Networks
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About the Authors