A multi-robot platform for the autonomous operation and maintenance of offshore wind farms

Sara Bernardini, Ferdian Jovan, Zhengyi Jiang, Simon Watson, Andrew Weightman, Peiman Moradi, Tom Richardson, Rasoul Sadeghian, Sina Sareh

Research output: Chapter in Book/Report/Conference proceedingChapter

14 Citations (Scopus)

Abstract

With the increasing scale of offshore wind farm development, maintaining farms efficiently and safely becomes a necessity. The length of turbine downtime and the logistics for human technician transfer make up a significant proportion of the operation and maintenance (OM) costs. To reduce such costs, future OM infrastructures will increasingly rely on offshore autonomous robotic solutions that are capable of co-managing wind farms with human operators located onshore. In particular, unmanned aerial vehicles, autonomous surface vessels and crawling robots are expected to play important roles not only to bring down costs but also to significantly reduce the health and safety risks by assisting (or replacing) human operators in performing the most hazardous tasks. This paper portrays a visionary view in which heterogeneous robotic assets, underpinned by AI agent technology, coordinate their behavior to autonomously inspect, maintain and repair offshore wind farms over long periods of time and unstable weather conditions. They cooperate with onshore human operators, who supervise the mission at a distance, via the use of shared deliberation techniques. We highlight several challenging research directions in this context and offer ambitious ideas to tackle them as well as initial solutions.
Original languageEnglish
Title of host publicationAAMAS '20: Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems
Place of PublicationSouth Carolina, US
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1696-1700
Number of pages5
ISBN (Electronic)9781450375184
Publication statusPublished - 13 May 2020
Externally publishedYes

Bibliographical note

This work has received funding from the UK’s innovation agency, Innovate UK, under Grant Agreement No.104821: “Multi-Platform Inspection Maintenance and Repair In Extreme Environment”.

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