Evolutionary robotics: from algorithms to implementations

This invaluable book comprehensively describes evolutionary robotics and computational intelligence, and how different computational intelligence techniques are applied to robotic system design.

It embraces the most widely used evolutionary approaches with their merits and drawbacks, presents some related experiments for robotic behavior evolution and the results achieved, and shows promising future research directions.

Clarity of explanation is emphasized such that a modest knowledge of basic evolutionary computation, digital circuits and engineering design will suffice for a thorough understanding of the material.The book is ideally suited to computer scientists, practitioners and researchers keen on computational intelligence techniques, especially the evolutionary algorithms in autonomous robotics at both the hardware and software levels.Sample Chapter(s)Chapter 1: Artificial Evolution Based Autonomous Robot Navigation (184 KB)Contents:Artificial Evolution Based Autonomous Robot NavigationEvolvable Hardware in Evolutionary RoboticsFPGA-Based Autonomous Robot Navigation via Intrinsic EvolutionIntelligent Sensor Fusion and Learning for Autonomous Robot NavigationTask-Oriented Developmental Learning for Humanoid RobotsBipedal Walking Through Reinforcement LearningSwing Time Generation for Bipedal Walking Control Using GA Tuned Fuzzy Logic ControllerBipedal Walking: Stance Ankle Behavior Optimization Using Genetic AlgorithmReadership: Researchers in evolutionary robotics, and graduate and advanced undergraduate students in computational intelligence.