Project details
Civil infrastructures (e.g. bridges, tunnels, underground assets) provide essential urban services, yet as they age they suffer from a variety of defects due to structural degradation and a lack of in-time maintenance.

Current inspection and condition assessment practices rely mainly on manual data capturing and analysis, which can be risky, time-consuming, and error-prone. With the fast development of digital technologies, there is a growing trend of research on improving infrastructure inspection with sensing devices such as Unmanned Aerial Vehicles (UAVs) and Internet of Things (IoTs). However, such inspection processes are not fully automated and need to be operated and controlled by human beings, which still requires extra working hours and training in relevant skills. In addition, accurate interpretation of inspection data requires a high level of experience and expertise.

Innovative research based on robotics and automation is desired to address challenges in infrastructure inspection and maintenance. PhD candidates are desired to explore topics related but not limited to the following areas:

Automated data interpretation. Advanced methods such as computer vision, artificial intelligence (AI), and machine learning, should be developed to interpret different types of sensing data (e.g. images, videos, point cloud, sensor signals, etc) and evaluate infrastructure conditions.
Development of a multi-sensory robotic system with the ability of real-time inspection and data transfer. The system is expected to navigate autonomously for inspecting infrastructure, and perform real-time data interpretation for condition assessment.
Digital twinning of infrastructure. Robust and automated approaches based on computer vision and AI need to be developed for creating digital twins of infrastructure in an efficient and reliable way.
Integration of heterogeneous data to facilitate infrastructure management and decision making. Approaches should be developed to integrate different types of data (e.g. captured by various devices and existing information from different sources or platforms), which would be used for supporting decision making in inspection and maintenance.
The specific research direction can be decided based on the applicant’s background and interests. The PhD candidate will establish a thorough understanding of challenges in infrastructure inspection and maintenance, and how innovative robotic and automation methods can be applied to transform the current industry. Highly motivated students who are enthusiastic about robotics and automation in the construction industry are desired. The candidate could have a background in any relevant subject, but experience or proficiency in programming would be an advantage.

The successful candidate will have the chance to conduct innovative research with leading researchers both within the UK and internationally. Highly competitive candidates can receive full/partial funding.