Symbiotic Multi-Robot Organisms - Reliability, Adaptability, Evolution

Title Page

Foreword

Acknowledgements

Contents

List of Contributors

Acronyms

Introduction

Concepts of Symbiotic Robot Organisms

From Robot Swarm to Artificial Organisms: Self-organization of Structures, Adaptivity and Self-development

Mono- and Multi- functional Artificial Self-organization

Collective Robotics: Problem of Structures

Adaptability and Self-development

Artificial Symbiotic Systems: Perspectives and Challenges

Towards a Synergetic Quantum Field Theory for Evolutionary, Symbiotic Multi-Robotics

Cooperative (Coherent) Operations between Fermionic Units

Individual Contributions of the Eigenanteile

Separate Perturbations of the Eigenanteile

Coupling of the Disturbed Eigenanteil Equations

Information Model and Interactions of Structured Components

Functional and Reliability Modelling of Swarm Robotic Systems

Macroscopic Probabilistic Modelling in Swarm Robotics

Reliability Modelling of Swarm Robotic Systems

Concluding Discussion

Heterogeneous Multi-Robot Systems

Reconfigurable Heterogeneous Mechanical Modules

A Heterogeneous Approach in Modular Robotics

Integration and Miniaturization

Locomotion Mechanisms

Docking Mechanisms and Strategies

Mechanical Degrees of Freedoms: Actuation for the Individual Robot and for the Organism

Tool Module: Active Wheel

Summary of the Three Robotic Platforms

Computation, Distributed Sensing and Communication

Electronic Architectures in Related Works

General Hardware Architecture in SYMBRION/REPLICATOR

General Sensor Capabilities

Vision and IR-Based Perception

Triangulation Laser Range Sensor for Obstacle Detection and Interpretation of Basic Geometric Features

Powerful Wireless Communication and 3D Real Time Localisation Systems

Integration Issues

Energy Autonomy and Energy Harvesting in Reconfigurable Swarm Robotics

Energy Autonomy

Energy Harvesting

Energy Trophallaxis

Energy Sharing within a Robot Organism

Energy Management

Modular Robot Simulation

Simulation Environments

The Symbricator3D Simulation Environment

Showcase: The Dynamics Predictor

Conclusion and Future Work

Cognitive Approach in Artificial Organisms

Cognitive World Modeling

Methodology

Spatial World Modeling

Evolution Map

Map

Jockeys

Reasoning

Executor

Porting the EMa onto a Robot

EMa Care-Taking Procedures

Physical Layout

Logical Layout and Communication

Experiments

Functional World Modelling

Emergent Cognitive Sensor Fusion

Scenarios

Towards Embodied and Emergent Cognition

Sensor Fusion Model

Application of Embodied Cognition to the Development of Artificial Organisms

Natural vs. Artificial Systems: Collectivity and Adaptability in Inanimated Nature

Definition of Information and Knowledge Related to Restrictions

Collectivity and Adaptability in Animated Nature

Information Based Learning to Develop and Maintain Artificial Organisms

Adaptive Control Mechanisms

General Controller Framework

Controller Framework in SYMBRION/REPLICATOR

Bio-inspiration for the Structure of Artificial Genome

Action Selection Mechanism

Overview of Different Control Mechanisms

Hormone-Based Control for Multi-modular Robotics

Micro-organisms’ Cell Signals and Hormones as Source of Inspiration

Related Work

Artificial Homeostatic Hormone System (AHHS)

Encoding an AHHS into a Genome

Self-organised Compartmentalisation

Evolutionary Adaptation

Single Robots

Forming Robot Organisms

Locomotion of Robot Organisms

Feedbacks

Conclusion

Evolving Artificial Neural Networks and Artificial Embryology

Shaping of ANN in Literature

Overview over Section

Concept of Adapting Virtual Embryogenesis for Controller Development

Diffusion Processes

Genetics and Cellular Behaviour

Simulated Physics

Cell Specialisation

Linkage

Depicting Genetic Structures and Feedbacks

Stable Growth due to Feedbacks in Genetic Structure

Developing Complex Shapes

The Growth of Neurons

Translation

Usability of Virtual Embryogenesis in the Context of Artificial Evolution for Shaping Artificial Neural Networks and Robot Controllers

Subsumption of Section

An Artificial Immune System for Robot Organisms

A Biological and Engineering Perspective

An Immune-inspired Architecture for Fault Tolerance in Swarm and Collective Robotic Systems

Innate Layer

Adaptive Layer

Summary

Structural Self-organized Control

Representation of Structures

Compact Representation: The Topology Generator

Scalability of Structures and Appearing Constraints

Morphogenesis as an Optimal Decision Problem

Self-organized Morphogenesis

Collective Memory and Further Points

Kinematics and Dynamics for Robot Organisms

Modeling of Multi-robot Organisms

Inverse Kinematics

Dynamics

Computational Analysis

Conclusion

Learning, Artificial Evolution and Cultural Aspects of Symbiotic Robotics

Machine Learning for Autonomous Robotics

Related Work

Challenges for ML-Based Robotics

The WOALA Scheme

First Experiments with WOALA

Discussion and Perspectives

Embodied, On-Line, On-Board Evolution for Autonomous Robotics

Controllers, Genomes, Learning, and Evolution

Classification of Approaches to Evolving Robot Controllers

The Classical Off-Line Approach Based on a Master EA

On-Line Approaches

Testing Encapsulated Evolutionary Approaches

Conclusions and Future Work

Artificial Sexuality and Reproduction of Robot Organisms

The Role of Sexuality for Robots

Artificial Reproduction

Implementation of Artificial Sexuality on Real Robots

Evolutionary Engineering

Evolution of Multicellular Organisms

Sex and Reproduction of Symbiotic Robots

Conclusion

Self-learning Behavior of Virus-Like Artificial Organisms

Effectiveness of Evolutionary Optimization for Genetic Cloud

Interaction between Evolution and Learning in an Evolutionary Process

Evolutionary Emergence of a Cooperation between Agents

Discovering of Chains of Actions by Self-learning Agents

Virus-Like Organisms: New Adaptive Paradigm ?

Towards the Emergence of Artificial Culture in Collective Robotic Systems

Project Aims

The Artificial Culture Laboratory

The Challenges and the Case for an Emerging Robot Culture

Robot Memes and Meme Tracking

Concluding Remarks

Final Conclusions

References

Index