Soft computing for intelligent control and mobile robotics

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This book provides a comprehensive exploration of hybrid intelligent systems utilizing soft computing techniques for intelligent control and mobile robotics. Soft Computing (SC) encompasses various intelligent computing paradigms, such as fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be effectively combined to address real-world challenges. The text showcases a variety of applications, particularly in intelligent control and mobile robotics, organized into five main sections. The first section focuses on theory and algorithms, introducing new models and concepts foundational for intelligent control and robotics. The second section emphasizes intelligent control, highlighting the use of bio-inspired techniques like evolutionary algorithms and neural networks to manage non-linear systems. The third section discusses the optimization of fuzzy controllers, exploring bio-inspired methods to automate the design of optimal type-1 and type-2 fuzzy controllers. The fourth section addresses the application of SC techniques in time series prediction and intelligent agents. Finally, the fifth section covers computer vision and robotics, presenting papers that apply soft computing methods to vision-related tasks and robotic applications. Each part contributes to a deeper understanding of how hybrid intelligent systems can be developed and implemented in various domains.