Mobile Robots: The Evolutionary Approach

1. Front Matter

   Pages I-XXI

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2. Evolutionary Mobile Robots

   1. Front Matter

      Pages 1-1

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   2. Differential Evolution Approach Using Chaotic Sequences Applied to Planning of Mobile Robot in a Static Environment with Obstacles

      • Leandro dos Santos Coelho, Nadia Nedjah, Luiza de Macedo Mourelle

      Pages 3-22

   3. Evolving Modular Robots for Rough Terrain Exploration

      • Olivier Chocron

      Pages 23-46

   4. Evolutionary Navigation of Autonomous Robots Under Varying Terrain Conditions

      • Terrence P. Fries

      Pages 47-62

   5. Aggregate Selection in Evolutionary Robotics

      • Andrew L. Nelson, Edward Grant

      Pages 63-88

   6. Evolving Fuzzy Classifier for Novelty Detection and Landmark Recognition by Mobile Robots

      • Plamen Angelov, Xiaowei Zhou

      Pages 89-118

3. Learning Mobile Robots

   1. Front Matter

      Pages 120-120

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   2. Reinforcement Learning for Autonomous Robotic Fish

      • Jindong Liu, Lynne E. Parker, Raj Madhavan

      Pages 121-135

   3. Module-based Autonomous Learning for Mobile Robots

      • Esther L. Colombini, Carlos H. C. Ribeiro

      Pages 137-159

   4. A Hybrid Adaptive Architecture for Mobile Robots Based on Reactive Behaviours

      • Antonio Henrique Pinto Selvatici, Anna Helena Reali Costa

      Pages 161-184

   5. Collaborative Robots for Infrastructure Security Applications

      • Yi Guo, Lynne E. Parker, Raj Madhavan

      Pages 185-200

   6. Imitation Learning: An Application in a Micro Robot Soccer Game

      • Dennis Barrios-Aranibar, Pablo Javier Alsina

      Pages 201-219

4. Back Matter

   Pages 221-223

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Mobile robotic is a recent ?eld that has roots in many engineering and science disciplines such as mechanical, electrical, mechatronics, cognitive and social sciences just to name few. A mobile robot needs e?cient mechanisms of lo- motion, kinematics, sensors data, localization, planning and navigation that enable it to travel throughout its environment. Scientists have been fascinated by conception of mobile robots for many years. Machines have been designed withwheelsandtracksorotherlocomotion devicesand/orlimbs topropelthe unit. When the environment is well ordered these machines can function well. Mobile robots have demonstrated strongly their ability to carry out useful work. Intelligent robots have become the focus of intensive research in the last decade. The ?eld of intelligent mobile robotics involves simulations and re- world implementations of robots which adapt themselves to their partially unknown, unpredictable and sometimes dynamic environments. The design and control of autonomous intelligent mobile robotic systems operatinginunstructuredchangingenvironmentsincludesmanyobjectived- ?culties. There are several studies about the ways in which, robots exhibiting some degree of autonomy, adapt themselves to ?t in their environments. The application and use of bio-inspired techniques such as reinforcement lea- ing, arti?cial neural networks, evolutionary computation, swarm intelligence and fuzzy systems in the design and improvement of robot designs is an em- gentresearchtopic. Researchershaveobtainedrobotsthatdisplayanamazing slew of behaviours and perform a multitude of tasks.

• Navigation
• architecture
• autonomous robot
• behavior
• cognition
• evolution
• evolutionary computation
• fuzzy
• learning
• mobile robot
• perception
• reinforcement learning
• robot
• robotics
• rough terrain

• Faculdade de Engenharia, Universidade do Estado do Rio de Janeiro, Maracanã, Brazil

  Nadia Nedjah, Luiza de Macedo Mourelle

• Pontifical Catholic University of Paraná, Curitiba, Brazil

  Leandro dos Santos Coelho

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