AI and Robotics for Autonomous Maintenance and Inspection Systems (ARAMIS)
Lead Research Organisation:
University of Kent
Department Name: Sch of Engineering & Digital Arts
Abstract
Mechanical inspection and maintenance operations across many UK industries such as aerospace, manufacturing, rail transport, renewable energy, oil and gas, water, etc. are rapidly being automized and operator free. Along with this rapid shift from manual inspection to advanced monitoring tools (such as AR tools or digital twins), many businesses are interested in deploying smart multi-sensor technologies including Artificial Intelligence (AI) and robotics and autonomous systems (RAS) to make their inspection and maintenance processes less time-consuming and a lot easier. This project aims to develop advanced data-driven artificial intelligence (AI) and machine learning (ML) technologies for the purpose of inspection and monitoring of mechanical assets and infrastructure using a wide range of robotic and autonomous systems including remotely operating vehicles (ROV) and unmanned aerial vehicles (UAV). These technologies will have the capability of being adapted to different UK industries and assist them in inspecting their critical assets remotely, collecting required information (in different formats) in near real-time and preventing incidents before happening.
Organisations
Publications
Macaulay M
(2022)
Machine learning techniques for robotic and autonomous inspection of mechanical systems and civil infrastructure
in Autonomous Intelligent Systems
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/T518141/1 | 30/09/2020 | 29/09/2025 | |||
2466663 | Studentship | EP/T518141/1 | 30/09/2020 | 29/09/2023 | Michael Macaulay |