| Description |
1 online resource (xv, 225 pages) |
| Series |
Studies in computational intelligence ; v. 341 |
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Studies in computational intelligence ; v. 341.
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| Contents |
Machine generated contents note: pt. I Introduction -- 1. Evolutionary Robotics: Exploring New Horizons / Vincent Padois -- 1.1. Introduction -- 1.2. Brief Introduction to Evolutionary Computation -- 1.3. When to Use ER Methods? -- 1.3.1. Absence of "Optimal" Method -- 1.3.2. Knowledge of Fitness Function Primitives -- 1.3.3. Knowledge of Phenotype Primitives -- 1.4. Where and How to Use EA in the Robot Design Process? -- 1.4.1. Mature Techniques: Parameter Tuning -- 1.4.2. Current Trend: Evolutionary Aided Design -- 1.4.3. Current Trend: Online Evolutionary Adaptation -- 1.4.4. Long Term Research: Automatic Synthesis -- 1.5. Frontiers of ER and Perspectives -- 1.5.1. Reality Gap -- 1.5.2. Fitness Landscape and Exploration -- 1.5.3. Genericity of Evolved Solutions -- 1.6. Roboticist Point of View -- 1.7. Discussion -- 1.7.1. Good Robotic Engineering Practices -- 1.7.2 |
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Note continued: 8.3. Genetic Algorithm and Implementation -- 8.3.1. Genetic Algorithm -- 8.3.2. Genome -- 8.3.3. Trajectory Tracking -- 8.3.4. Control Law -- 8.3.5. Indicators -- 8.4. Results -- 8.4.1. Design with Simple Trajectory -- 8.4.2. Design with Complex Trajectory -- 8.5. Conclusions and Future Works -- 8.5.1. Conclusions -- 8.5.2. Future Works -- References -- 9. Multi-cellular Based Self-organizing Approach for Distributed Multi-Robot Systems / Yaochu Jin -- 9.1. Introduction -- 9.2. Biological Background -- 9.3. Approach -- 9.3.1. GRN-Based Dynamics -- 9.3.2. Convergence Analysis of System Dynamics -- 9.3.3. Evolutionary Algorithm for Parameter Tuning -- 9.4. Simulation and Results -- 9.4.1. Case Study 1 Multi-robots Forming a Unit Circle -- 9.4.2. Case Study 2 Multi-robots Forming a Unit-Square -- 9.4.3. Case Study 3 Self-reorganization -- ̂ 9.4.4. Case Study 4 Robustness Tests to Sensory Noise -- 9.4.5. Case Study 5 Self-adaptation to Environmental Changes -- 9.5. Conclusion and Future Works -- References -- 10. Novelty-Based Multiobjectivization / Jean-Baptiste Mouret -- 10.1. Introduction -- 10.2. Related Work -- 10.2.1. Novelty Search -- 10.2.2. Multi-Objective Evolutionary Algorithms -- 10.2.3. Multiobjectivization -- 10.3. Method -- 10.3.1. Experiment -- 10.3.2. Fitness Function and Distance between Behaviors -- 10.3.3. Variants -- 10.3.4. Expected Results -- 10.3.5. Experimental Parameters -- 10.4. Results -- 10.4.1. Average Fitness -- 10.4.2. Convergence Rate -- 10.4.3. Exploration -- 10.5. Conclusion and Discussion -- References -- 11. Embedded Evolutionary Robotics: The (1+1)-Restart-Online Adaptation Algorithm / Nicolas Bredeche -- 11.1. Introduction -- 11.2. Extending the (1+1)-Online EA -- 11.2.1. Limits of (1+1)-Online -- 11.2.2. (1+1)-Restart-Online Algorithm |
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Note continued: 11.3. Experiments and Results -- 11.3.1. Hardware Set-Up -- 11.3.2. Experimental Set-Up -- 11.3.3. Experimental Results -- 11.3.4. Hall-of-Fame Analysis -- 11.3.5. Real Robot Experiment -- 11.4. Conclusion and Perspectives -- References -- 12. Automated Planning Logic Synthesis for Autonomous Unmanned Vehicles in Competitive Environments with Deceptive Adversaries / Satyandra K. Gupta -- 12.1. Introduction -- 12.2. USV System Architecture -- 12.2.1. USV Virtual Sensor Models -- 12.2.2. Planning Architecture -- 12.3. Planning Logic Synthesis -- 12.3.1. Test Mission -- 12.3.2. Synthesis Scheme -- 12.3.3. Planning Logic Components Evolution -- 12.4. Computational Experiments -- 12.4.1. General Setup -- 12.4.2. Results -- 12.5. Conclusions -- References -- 13. Major Feedback Loops Supporting Artificial Evolution in Multi-modular Robotics / Karl Crailsheim -- 13.1. Introduction -- 13.2. Artificial Homeostatic Hormone System -- 13.2.1. Artificial Genome -- 13.3. Feedback 1: Classic Control -- 13.4. Feedback 2: Learning -- 13.5. Feedback 3: Evolution -- 13.6. Feedback 4: Controller Morphogenesis -- 13.7. Feedback 5: Robot Organism Morphogenesis -- 13.8. Feedback 6: Body Motion -- 13.8.1. Step 1: The First Oscillator -- 13.8.2. Step 2: Motion of Bigger Organisms -- 13.8.3. Step 3: Motion of More Complex Organisms -- 13.9. Discussion -- References -- 14. Evolutionary Design and Assembly Planning for Stochastic Modular Robots / Hod Lipson -- 14.1. Introduction -- 14.2. Target Structure Evolution -- 14.3. Stochastic Fluidic Assembly System Model -- 14.4. Assembly Algorithm -- 14.5. Conclusion |
| Summary |
Evolutionary Algorithms (EAs) now provide mature optimization tools that have successfully been applied to many problems, from designing antennas to complete robots, and provided many human-competitive results. In robotics, the integration of EAs within the engineer's toolbox made tremendous progress in the last 20 years and proposes new methods to address challenging problems in various setups: modular robotics, swarm robotics, robotics with non-conventional mechanics (e.g. high redundancy, dynamic motion, multi-modality), etc. This book takes its roots in the workshop on "New Horizons in Evolutionary Design of Robots" that brought together researchers from Computer Science and Robotics during the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2009) in Saint Louis (USA). This book features extended contributions from the workshop, thus providing various examples of current problems and applications, with a special emphasis on the link between Computer Science and Robotics. It also provides a comprehensive and up-to-date introduction to Evolutionary Robotics after 20 years of maturation as well as thoughts and considerations from several major actors in the field. This book offers a comprehensive introduction to the current trends and challenges in Evolutionary Robotics for the next decade |
| Bibliography |
Includes bibliographical references |
| Notes |
Print version record |
| In |
Springer eBooks |
| Subject |
Evolutionary robotics -- Congresses
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Engineering.
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Artificial intelligence.
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Engineering
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Artificial Intelligence
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engineering.
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artificial intelligence.
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Evolutionary robotics.
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Ingénierie.
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Evolutionary robotics
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| Genre/Form |
proceedings (reports)
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Conference papers and proceedings
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Conference papers and proceedings.
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Actes de congrès.
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| Form |
Electronic book
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| Author |
Doncieux, Stéphane.
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Bredèche, Nicolas
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Mouret, Jean-Baptiste, 1981-
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| ISBN |
9783642182723 |
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3642182720 |
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3642182712 |
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9783642182716 |
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