Cyber-physical-human systems for mobile robots in energy asset management: Current practices and future opportunities

Abstract

Rapid advancement of digital technologies has resulted in an acceleration of cyber–physical systems for autonomous mobile robots to improve energy asset management activities within inspection, maintenance and repair. Within this systems-based approach, the role of the human-in-the-loop has also increased leading to cyber–physical-human systems requiring real-time interaction of robotics and digital twins with a human operator. Subject to existing network systems and physical systems, cyber–physical-human systems face enormous challenges requiring further investigation. This review presents the state-of-the-art in discovery, design, development and deployment of cyber–physical-human systems for mobile robots in energy asset management. To address dominant concepts and misconceptions in this area, key terminologies, system concepts and applications are presented. Then a state-of-the-art review with associated trends for several applications within academic and industrial sectors is presented where current practises and limitations are then discussed. Finally, future opportunities are explored alongside highlighted concepts providing a pathway for rapid adoption and improved key performance indicators of mobile fleets for facility operators and those in the wider community. • This review delivers a pioneering, systems-level framework that integrates mobile robotics, digital twins and human-in-the-loop mechanisms, addressing the complexities of energy asset management. • A concise critical review outlining current implementations, technological bottlenecks, and emerging patterns positioning CPHS as a transformative paradigm in energy infrastructure. • By introducing a new hierarchical classification of digital twins and rigorously defining core CPHS terms (e.g., digital tissue, cognitive twin, human–robot interaction modalities), the paper addresses the prevalent confusion and accelerates common understanding for academia, industry, and policymakers. • The review emphasizes resilience, verification, and cybersecurity as pressing challenges, while proposing future-forward solutions including federated learning, symbiotic system-of-systems architectures, and cognitive digital twins to future-proof robotic deployment at scale.