Multi-Agent Optimization for Offshore Wind Farm Inspection using an Improved Population-based Metaheuristic

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2020

Autores

Silva, RJ (Autor) Outra; Leite, PN (Autor) Outra; Pinto, AM (Autor) FEUP

Ata de Conferência Internacional

Título: 2020 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2020, Ponta Delgada, Portugal, April 15-17, 2020

Páginas: 53-60

2020 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2020

15 April 2020 through 16 April 2020

Indexação

ISI Web of Knowledge - 2 Citações

Scopus - 3 Citações

Outras Informações

ID Authenticus: P-00S-9Q2

DOI: 10.1109/icarsc49921.2020.9096107

Abstract (EN): The use of robotic solutions in tasks such as the inspection and monitorization of offshore wind farms aims to, not only mitigate the involved risks, but also to reduce the costs of operating and maintaining these structures. Performing a complete inspection of the platforms in useful time is crucial. Therefore, multiple agents can prove to be a cost-effective solution. This work proposes a trajectory planning algorithm, based on the Ant Colony metaheuristic, capable of optimizing the number of Autonomous Surface Vehicles (ASVs) to be used, and their corresponding route. Experiments conducted on a simulated environment, representative of the real scenario, proves this approach to be successful in planning a trajectory that is able to select the appropriate number of agents and the trajectory of each agent that avoids collisions and at the same time guarantees the full observation of the offshore structures.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 8