Human-Centric Robotics and Collaborative AI Systems for Adaptive Manufacturing and Healthcare Applications

Abstract

The integration of human-centric robotics and collaborative artificial intelligence (AI) systems is transforming modern manufacturing and healthcare environments. Unlike traditional automation, human- centric systems emphasize interaction, adaptability, and safety, enabling seamless collaboration between
humans and robots. This paper proposes an advanced framework for collaborative robotic systems that integrates AI-driven perception, real-time decision-making, and adaptive control mechanisms. The framework utilizes machine learning algorithms, computer vision, and sensor fusion to enable robots to understand human intentions and dynamically adjust their actions. In manufacturing, the system enhances productivity by enabling flexible and adaptive workflows, while in healthcare, it supports assistive robotics and precision interventions. Experimental simulations demonstrate improved task efficiency, reduced human
workload, and enhanced safety in collaborative environments. The results indicate that AI-driven collaborative systems significantly outperform conventional robotic systems in dynamic and unstructured settings. Furthermore, the integration of explainable AI improves system transparency and trust in human-robot interactions. This research contributes to the development of intelligent, safe, and adaptive robotic systems aligned with Industry 5.0 principles, emphasizing human-machine collaboration and sustainable
innovation.