Mario Gianni

Senior Lecturer in Robotics and Autonomous Systems

University of Liverpool
Country flagUnited Kingdom

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

UNITED KINGDOM
View details

Amir Aly

Lecturer in computer science (AI and Robotics)

University of Plymouth

UNITED KINGDOM
View details

MARCO PALOMINO

Associate Professor

University of Plymouth

UNITED KINGDOM
View details

Keri Collins

University of Plymouth

UNITED KINGDOM
View details

Asiya Khan

University of Plymouth

UNITED KINGDOM
View details

Hooman Samani

University of Hertfordshire

UNITED KINGDOM
View details

Ioanna Giorgi

Lecturer in Artificial Intelligence

University of Kent

UNITED KINGDOM
View details
ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.