2022· International Journal of Intelligent Automation & Robotics Engineering· 0 citations
TL;DR
The proposed framework integrates robotic navigation, visual sensing, image processing, defect classification, and maintenance decision support to achieve reliable inspection across diverse industrial sectors and supports predictive maintenance, improves quality assurance, and advances smart manufacturing in Industry 4.0.
Abstract
Autonomous robotic surface inspection combines intelligent robotics with computer vision to enable accurate, real-time, and contactless detection of surface defects such as cracks, corrosion, scratches, dents, and coating degradation. Unlike manual inspection, it improves consistency, enhances safety, reduces inspection time, and lowers operational costs. By integrating AI, deep learning, edge computing, IIoT, and Digital Twin technologies, autonomous robots can navigate complex industrial environments, capture high-resolution images, and perform automated defect analysis with minimal human intervention. The proposed framework integrates robotic navigation, visual sensing, image processing, defect classification, and maintenance decision support to achieve reliable inspection across diverse industrial sectors. This approach supports predictive maintenance, improves quality assurance, and advances smart manufacturing in Industry 4.0.
Machine vision has become a key technology in modern industrial automation, enabling fully automated quality inspection in robotic manufacturing systems. Unlike traditional human inspection methods, machine vision offers higher accuracy, consistency, speed, and lower operational costs. These systems use cameras, lighti...
Louis Pouzin, J. Arsac· International Journal of Int...· 0 citations
Experimental evaluation demonstrates significant improvements in inspection accuracy, fault classification, decision-making, maintenance prediction, reduced downtime, and lower human intervention, providing a foundation for next-generation intelligent industrial automation.
O. Dahl, K. Nygaard· International Journal of Mod...· 0 citations
A DNN-based vision-guided robotic assembly framework that integrates computer vision, intelligent decision-making, and real-time robotic control is proposed, supporting flexible automation and next-generation smart manufacturing in Industry 4.0 environments.
O. Dahl, K. Nygaard· International Journal of Int...· 0 citations
AI-based computer vision plays a central enabling role in intelligent quality inspection within the context of Industry 5.0, and can outperform traditional rule-based or manual solutions in terms of inspection accuracy, consistency, and throughput when they are supported by reliable acquisition, representative data, an...
Maaz A. Khan, C. Vasques, A. Cavadas· Encyclopedia· 0 citations
The proposed autonomous calibration framework integrates multi-sensor fusion, machine vision, laser measurement, inertial sensing, machine learning, and adaptive optimization to continuously estimate and compensate for calibration errors in real time to enable self-learning, real-time robotic calibration that supports...
Seshagiri N· International Journal of Int...· 0 citations
Rapid urbanization, industrialization, and aging infrastructure have increased the need for efficient monitoring systems. Traditional manual inspections of bridges, tunnels, pipelines, dams, railway tracks, and industrial facilities are costly, time-consuming, labor-intensive, and risky. Autonomous inspection robots of...
Pooja Agarwal, Rakesh Chandra· International Journal of Int...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
