The chasm between the physical capabilities of Intelligent Robotics and Autonomous Systems (IRAS) and their cognitive potential presents a formidable challenge. While these machines exhibit astonishing strength, precision, and speed, their intelligence and adaptability lag far behind. This inherent limitation obstructs the realization of autonomous systems that could reshape industries, from self-driving vehicles to industrial automation. The solution to this dilemma is unveiled within the pages of Modeling, Simulation, and Control of AI Robotics and Autonomous Systems. Find within the pages of this book answers for the cognitive deficit within IRAS. While these systems boast remarkable physical capabilities, their potential for intelligent decision-making and adaptation remains stunted, thereby bringing innovation to a halt. Solving this issue would mean the re-acceleration of multiple industries that could utilize automation to prevent humans from needing to do work that is dangerous, and could revolutionize transportation, and more. This comprehensive volume delves deep into the intricacies of IRAS, addressing the integration of artificial intelligence into robotics, machine vision, computational intelligence, sensors and actuators, and human-robot interactions. By offering cutting-edge insights and theoretical techniques, this book provides the pathway to the development of advanced robots and autonomous systems. These innovations are poised to usher in an era where the annual economic impact of these technologies will rival that of the mobile internet, advanced materials, and energy markets by 2025. For academics, scholars, and researchers, this book serves as a powerful catalyst for unlocking the untapped potential of IRAS, heralding a transformative revolution in the field. Modeling, Simulation, and Control of AI Robotics and Autonomous Systems offers an innovative solution that beckons to scholars, academicians, industrialists, and researchers.