Robotics, Artificial Intelligence and Autonomous Systems for Intelligent Maintenance and Asset Management

Industrial maintenance is undergoing a rapid transformation driven by advances in robotics, artificial intelligence (AI), autonomous systems, sensing technologies, and digitalization. While robotic automation has become well established in manufacturing, maintenance operations remain largely dependent on manual labour despite representing a significant proportion of operational costs across industries. Many maintenance activities continue to expose workers to hazardous environments, repetitive tasks, confined spaces, and ergonomically challenging conditions. At the same time, industries are facing increasing pressure to improve productivity, reduce downtime, enhance safety, and address shortages of skilled maintenance personnel. Recent advances in collaborative robots, mobile manipulators, drones, autonomous vehicles, machine vision, digital twins, Internet of Things (IoT), and AI-based perception and planning have created new opportunities to automate maintenance operations that were previously considered unsuitable for robotic systems. However, significant challenges remain in developing robust solutions capable of operating in unstructured environments and interacting safely with existing industrial assets and maintenance procedures. This Research Topic aims to bring together researchers and practitioners developing the next generation of robotic and AI-enabled maintenance technologies across a broad range of industrial sectors.The adoption of industrial robots continues to grow worldwide, with robot density reaching record levels and automation becoming a key driver of productivity and economic growth. Robotics has demonstrated substantial benefits in manufacturing, construction, logistics, healthcare, energy, mining, offshore operations, and nuclear industries. Similar opportunities exist for maintenance applications, where intelligent robotic systems can improve safety, consistency, efficiency, and asset reliability. Despite considerable progress, maintenance remains one of the least automated industrial activities. Existing maintenance tools and procedures are generally designed for human operators rather than robotic systems. Variations in component position, accessibility, environmental conditions, sensing uncertainty, and task complexity continue to limit widespread deployment. Addressing these challenges requires advances in robot design, perception, manipulation, AI planning, human-robot collaboration, and adaptive maintenance tools.This Research Topic welcomes original research, review papers, case studies, perspectives, and technology reports covering, but not limited to: Robotic inspection and maintenance; AI for predictive and autonomous maintenance; Collaborative robots for maintenance operations; Mobile manipulation and autonomous maintenance robots; Railway, aerospace, automotive, power systems, energy, construction and nuclear maintenance robotics; AI planning and decision-making for maintenance; Digital twins and IoT for intelligent maintenance; Computer vision and sensor fusion; Robot-friendly maintenance tools and end-effectors; Human-robot collaboration; Multi-robot maintenance systems; Maintenance task planning and scheduling; Learning from demonstration for maintenance robots; Maintenance benchmarking and industrial case studies; Safety, standards and certification for maintenance robotics; Real-world deployment and technology transfer; Condition monitoring. Topic editors: Hamideza Fahham, Dominique Blouin, Yongbin Liu, Mohammad Reza Salehizadeh Source: https://www.frontiersin.org/research-topics/84046/robotics-artificial-intelligence-and-autonomous-systems-for-intelligent-maintenance-and-asset-management