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Smart Robotic Systems for Hazardous Industrial Environments

2018 · International Journal of Intelligent Automation & Robotics Engineering · 0 citations

TL;DR

Overall, intelligent robotics can significantly reduce human exposure, improve inspection quality, and enable early fault detection, while future research must focus on certifiable AI, resilient perception, and standardized benchmarking in hazardous environments.

Abstract

Industrial environments such as petrochemical plants, offshore platforms, mines, and nuclear facilities pose severe risks to human workers, including toxic exposure, explosions, radiation, and extreme conditions. To achieve safer, zero-harm operations, intelligent robotic systems are increasingly deployed for inspection, monitoring, and emergency response in hazardous or inaccessible areas. Recent advancements in multi-modal sensing, autonomous navigation, and industrial connectivity have transformed robots into capable cyber-physical agents.This paper presents an IEEE-style overview of intelligent robots in hazardous industries, structured across platform, perception, decision, communication, and assurance layers. It introduces a Risk-Aware Autonomy (RAA) framework that balances task success with safety constraints using optimization-based control. The study also highlights real-world challenges such as harsh environments, limited reliability of AI models, and certification complexities. Furthermore, the paper outlines a systematic engineering methodology covering hazard analysis, system design, validation, and operational governance. It emphasizes dual assurance—integrating safety and cybersecurity to ensure reliable deployment. Overall, intelligent robotics can significantly reduce human exposure, improve inspection quality, and enable early fault detection, while future research must focus on certifiable AI, resilient perception, and standardized benchmarking in hazardous environments.

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