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A Multi-Robot Platform for the Autonomous Operation and Maintenance of Offshore Wind Farms

Published: 13 May 2020 Publication History

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 (O&M) costs. To reduce such costs, future O&M 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.

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Cited By

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  • (2024)Mapping the Complexity of Legal Challenges for Trustworthy Drones on Construction Sites in the United KingdomACM Journal on Responsible Computing10.1145/36646171:3(1-26)Online publication date: 22-Jul-2024

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Published In

cover image ACM Conferences
AAMAS '20: Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems
May 2020
2289 pages
ISBN:9781450375184

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International Foundation for Autonomous Agents and Multiagent Systems

Richland, SC

Publication History

Published: 13 May 2020

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Author Tags

  1. ai planning
  2. autonomy
  3. explainability
  4. extreme environments
  5. multi-agency
  6. robotics
  7. wind farms

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  • Research-article

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  • Innovate UK

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AAMAS '19
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Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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View all
  • (2024)Mapping the Complexity of Legal Challenges for Trustworthy Drones on Construction Sites in the United KingdomACM Journal on Responsible Computing10.1145/36646171:3(1-26)Online publication date: 22-Jul-2024

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