Autonomous Systems and Robotics: An Overview of AI-Powered Innovations
Keywords:
AI-driven robotics, Computer Vision, Natural Language Processing (NLP), Decision-Making Algorithms, Sensor FusionAbstract
The integration of Artificial Intelligence (AI) into autonomous systems and robotics has transformed traditional automation into intelligent, adaptive, and self-governing technologies. This review paper examines the evolution of robotics from rule-based mechanical systems to AI-powered platforms capable of perception, decision-making, and real-time adaptability. It highlights core enabling technologies, including machine learning, computer vision, natural language processing, sensor fusion, and reinforcement learning, which collectively empower autonomous robots across domains such as healthcare, manufacturing, logistics, and autonomous vehicles. The study synthesizes recent literature addressing technological advancements, operational efficiencies, and measurable performance improvements, particularly in industrial and clinical settings. Furthermore, it explores emerging integrations with IoT, smart infrastructure, and Industry 4.0/5.0 ecosystems. Alongside these innovations, critical challenges such as safety, cybersecurity, ethical governance, scalability, interoperability, and regulatory compliance are discussed. The review provides a comprehensive understanding of AI-driven robotics and outlines future research directions toward developing secure, human-centered, and trustworthy autonomous systems.
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