Calendar An icon of a desk calendar. Cancel An icon of a circle with a diagonal line across. Caret An icon of a block arrow pointing to the right. Email An icon of a paper envelope. Facebook An icon of the Facebook "f" mark. Google An icon of the Google "G" mark. Linked In An icon of the Linked In "in" mark. Logout An icon representing logout. Profile An icon that resembles human head and shoulders. Telephone An icon of a traditional telephone receiver. Tick An icon of a tick mark. Is Public An icon of a human eye and eyelashes. Is Not Public An icon of a human eye and eyelashes with a diagonal line through it. Pause Icon A two-lined pause icon for stopping interactions. Quote Mark A opening quote mark. Quote Mark A closing quote mark. Arrow An icon of an arrow. Folder An icon of a paper folder. Breaking An icon of an exclamation mark on a circular background. Camera An icon of a digital camera. Caret An icon of a caret arrow. Clock An icon of a clock face. Close An icon of the an X shape. Close Icon An icon used to represent where to interact to collapse or dismiss a component Comment An icon of a speech bubble. Comments An icon of a speech bubble, denoting user comments. Ellipsis An icon of 3 horizontal dots. Envelope An icon of a paper envelope. Facebook An icon of a facebook f logo. Camera An icon of a digital camera. Home An icon of a house. Instagram An icon of the Instagram logo. LinkedIn An icon of the LinkedIn logo. Magnifying Glass An icon of a magnifying glass. Search Icon A magnifying glass icon that is used to represent the function of searching. Menu An icon of 3 horizontal lines. Hamburger Menu Icon An icon used to represent a collapsed menu. Next An icon of an arrow pointing to the right. Notice An explanation mark centred inside a circle. Previous An icon of an arrow pointing to the left. Rating An icon of a star. Tag An icon of a tag. Twitter An icon of the Twitter logo. Video Camera An icon of a video camera shape. Speech Bubble Icon A icon displaying a speech bubble WhatsApp An icon of the WhatsApp logo. Information An icon of an information logo. Plus A mathematical 'plus' symbol. Duration An icon indicating Time. Success Tick An icon of a green tick. Success Tick Timeout An icon of a greyed out success tick. Loading Spinner An icon of a loading spinner.

Edinburgh scientists developing robots to clean train carriages

© Kris Miller / DCT MediaPost Thumbnail

Robots that can clean train carriages and drones to inspect railway bridge arches are being developed by scientists in two new research projects.

The Heriot-Watt University researchers are working on robotised mobile inspection platforms that can operate in hard-to-reach areas such as between and under the seats of a train carriage.

The robot platforms will detect hazards using an innovative algorithm and pick up rubbish such as discarded newspapers as well as dangerous items such as needles and blades.

The second project will develop autonomous drone technology to inspect railway bridge archways, particularly the inner curve which is difficult to access.

Scientists at Heriot-Watt University in Edinburgh are working in partnership with rail industry body the Rail Safety and Standards Board (RSSB) on the projects.

Dr Mustafa Suphi Erden of Heriot-Watt University, who is leading the research, said: “Initially our work will focus on developing a robotic mobile platform that can autonomously navigate in the confined space in between and under the seats of a train carriage.

“We will then develop an algorithm to detect cleaning and hazardous situations using a detailed set of train carriage images.

“We will also be creating a manipulator to integrate with the mobile platform to collect predefined objects regularly dropped or discarded by rail passengers such as bottles, paper cups, newspapers, and also biologically dangerous objects such as blades, needles, and injectors left behind by the passengers.”

In the other project, scientists will develop drones which will collect images autonomously under the arches and will then automatically analyse the pictures to detect defects in the structure such as cracks, flakes, water seepage, insufficient mortar and misalignment.

Dr Erden said: “Our work will initially focus on developing the drone technology that can navigate itself using proximity sensors and webcams.

“These will allow the drone to control itself from one edge of the arch to the other through a horizontal line and turn back to follow a parallel path on another horizontal line.

“This level of accuracy, including maintaining an accurate distance from the surface of the arch, means every inch of the arch will be inspected in detail.

“We will then develop a machine learning algorithm to inspect the collected images and to detect a pre-identified set of hazards in the brickwork of the bridges.”

RSSB is funding two four-year PhD studentships based at Heriot-Watt University.

Giulia Lorenzini, RSSB’s Senior Partnerships and Grants Manager, said: “The rail industry is only just starting to get to grips with what Robotics and Autonomous Systems (RAS) applications have to offer.

“It’s great to be working with a leading research institution in the field so that our members in rail can see evidence of the technology’s potential in a functioning, practical way.”