by Lingfeng Wang (Texas A&M University, USA) , Kay Chen Tan (National University of Singapore, Singapore) , & Chee Meng Chew (National University of Singapore, Singapore)

Table of Contents (71k)
Chapter 1: Artificial Evolution Based Autonomous Robot Navigation (184k)

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.

• Artificial Evolution Based Autonomous Robot Navigation
• Evolvable Hardware in Evolutionary Robotics
• FPGA-Based Autonomous Robot Navigation via Intrinsic Evolution
• Intelligent Sensor Fusion and Learning for Autonomous Robot Navigation
• Task-Oriented Developmental Learning for Humanoid Robots
• Bipedal Walking Through Reinforcement Learning
• Swing Time Generation for Bipedal Walking Control Using GA Tuned Fuzzy Logic Controller
• Bipedal Walking: Stance Ankle Behavior Optimization Using Genetic Algorithm