Bram Ton Graduates with PhD on Digital Representations of Rail Infrastructure for Predictive Maintenance and Robotics

We are thrilled to announce that Bram Ton, a PhD graduate from both the Pervasive Systems group at the University of Twente and Saxion University of Applied Sciences, has successfully defended his thesis. His research introduces an innovative methodology for creating digital representations of rail infrastructure, which supports efficient maintenance and construction tasks and contributes to advancements in predictive maintenance and robotic construction.

As demand for sustainable transportation increases, so does the pressure on existing rail systems. Bram’s research focuses on leveraging point cloud data collected using mobile laser scanners to generate detailed and up-to-date digital models of railway infrastructure. These models are essential for maintenance planning and construction tasks, with the potential to further enable automation and improve system resilience.

His work also explores the use of object detection and semantic segmentation methods to identify and localize key assets within the rail environment, and investigates the potential for immersive visualization through head-mounted displays, offering a new way to interact with and engage with the digital representations of the infrastructure.

A big congratulations to Bram on this amazing accomplishment!