Robotics and Intelligent Systems for Autonomous Industrial Operations: Architectures, Algorithms, and Real-World Applications

Abstract

The use of robotics and intelligent system within industrial process is revolutionizing the manufacturing, logistics, inspection and maintenance activities by offering very high degrees of autonomy, operational efficiency and safety within a workplace. The aim of this paper is to outline detailed review of the backbone architecture, algorithms and their practical implementations in the world that propel autonomous industry. We discuss enabling technologies such as robotic modules of robotic clothing, augmented and virtual reality perception systems, decentralized control structures with a hybrid architecture and AI-based decision-making systems. The methodological synthesis of the paper is based on the latest results in perception and mapping, motion planning, multi-agent coordination, and predictive maintenance, as well as human-robot collaboration protocols at the level of the existing safety standards. Incorporating performance positives, issues around integration and operations, along with case studies based on real-world application, analysis is performed due to autonomous warehousing and adaptive assembly lines, and offshore inspection robotics. According to the results of literacy and industry reports, it has been documented that throughput, defect detection and asset utilization has increased significantly and downtime, as well as human exposure to dangerous environments, has decreased. We also find recurrent difficulties, in particular, generalization of tasks and safe human-robot interaction under dynamic environments, cyber security in interconnected robotic flock. Future research directions to autonomous self-adapting and sustainable industrial ecosystems able to operate resilient and scalable in Industry 4.0 and beyond are described at the end of the paper as the conclusion.