Mario Gianni
Senior Lecturer in Robotics and Autonomous Systems
Research Interests
Explore related searches
Contact this professor
Get a free first email built on one of their papers, ready for you to edit and send yourself.
About
Dr. Mario Gianni is a Senior Lecturer in Robotics and Autonomous Systems at the University of Liverpool, UK. His research focuses on the intersection of robotics and health technology, offshore wind turbine inspection, and machine learning applications. Notable recent articles include explorations of robot-assisted healthcare for older adults and advanced methodologies for multi-robot coverage path planning in offshore environments.
Articles (5)
Year:
2024
Year:
2024
Year:
2023
Offshore wind turbine (OWT) inspection research is receiving increasing interest as the sector grows worldwide. Wind farms are far from emergency services and experience extreme weather and winds. This hazardous environment lends itself to unmanned approaches, reducing human exposure to risk. Increasing automation in inspections can reduce human effort and financial costs. Despite the benefits, research on automating inspection is sparse. This work proposes that OWT inspection can be described as a multi-robot coverage path planning problem. Reviews of multi-robot coverage exist, but to the best of our knowledge, none captures the domain-specific aspects of an OWT inspection. In this paper, we present a review on the current state of the art of multi-robot coverage to identify gaps in research relating to coverage for OWT inspection. To perform a qualitative study, the PICo (population, intervention, and context) framework was used. The retrieved works are analysed according to three aspects of coverage approaches: environmental modelling, decision making, and coordination. Based on the reviewed studies and the conducted analysis, candidate approaches are proposed for the structural coverage of an OWT. Future research should involve the adaptation of voxel-based ray-tracing pose generation to UAVs and exploration, applying semantic labels to tasks to facilitate heterogeneous coverage and semantic online task decomposition to identify the coverage target during the run time.
Year:
2023
Year:
2022
Collaborators (7)
Sanjay Sharma
University of Plymouth
Amir Aly
Lecturer in computer science (AI and Robotics)
University of Plymouth
MARCO PALOMINO
Associate Professor
University of Plymouth
Keri Collins
University of Plymouth
Asiya Khan
University of Plymouth
Hooman Samani
University of Hertfordshire
Ioanna Giorgi
Lecturer in Artificial Intelligence
University of Kent
Make your next move.
Prepare your application
Review drafts before you send them.