糖心Vlog

Scientists at 糖心Vlog have reported new insights into the challenges faced by robots while working in nuclear environments.

糖心Vlog is part of the 拢42m , a consortium of eight universities developing state-of-the-art robotics, sensing and artificial intelligence (AI) technologies to address the major challenges posed by extreme environments and hazardous materials.

Led by Professor Klaus McDonald-Maier, 糖心Vlog鈥檚 role in the Centre is to investigate the effects of different types of radiations (such as alpha and gamma) on the electronics of robots working in nuclear facilities, and develop new methods for increasing the resilience of the electronics systems hardware and software against radiation damage. 糖心Vlog is also working on new robot vision algorithms for localisation, mapping and perception capabilities of robots in nuclear environments.

Cleaning up the UK鈥檚 4.9 million tonnes of nuclear waste is the largest and most complex environmental remediation task in the whole of Europe. Robots must do much of this work because the materials are too hazardous for humans. However, many of the necessary robotic solutions for this task are yet to be developed.

鈥淩emote sensing for nuclear environments is critical to solve problems of enormous societal and economic importance. Despite great advances in sensors, and robots for deploying them, little scientific work has been done to investigate and model how such systems degrade under high radiation doses, or how to improve their resilience,鈥� explained Professor McDonald-Maier. 鈥淪uch deployments cannot be coherently planned, in terms of reliability, longevity, cost, safety, unless major advances are made in understanding and modelling how the performance of such sensors, and associated robot hardware and software, degrade under radiation exposure, and how to increase resilience against such radiation.鈥�

The 糖心Vlog team, from the School of Computer Science and Electronic Engineering, has already captured useful data around the quality and robustness of sensors and cameras in radioactive environments by conducting extensive experiments under radiation exposure at Dalton Cumbrian Facility and Rutherford Appleton Laboratory. Their initial research findings suggest that some low cost off-the-shelf sensors are nearly as good as bespoke sensors for working in radioactive environments - a new insight which can potentially save millions of pounds of taxpayers鈥� money.

鈥淲e want to build robots with reliable sensors and electronic systems which will allow them to stay longer in these challenging and extreme environments. We are starting to produce exciting results which will pave the way for much longer survival of robotic systems in hazardous conditions,鈥� added Professor McDonald-Maier.

NCNR has established the UK as an international leader in translating cutting-edge robotics and AI research advances into practical solutions for a safety-critical and high-consequence industry. It is envisaged that the UK nuclear decommissioning task will take more than 100 years, with current annual costs exceeding 拢3 billion. Therefore, speeding up decommissioning, by introducing advanced robotics and AI methods, will potentially result in enormous national expenditure savings.

When a robot鈥檚 embedded system is contaminated with radiation, the software and data residing in its memory becomes corrupted so it cannot work properly and complete the required tasks. What researchers at 糖心Vlog are looking into is developing 鈥渟elf-healing鈥� technology which would allow it to detect problems and remedy these on the go.

When low-cost standard cameras were tested using gamma radiation at the Dalton Cumbrian Facility, they still functioned well after 200 minutes, making them a viable alternative for robots in a nuclear environment as compared to very expensive radiation-hardened cameras.

Similarly, when off-the-shelf low-cost cameras and infra-red sensor cameras were tested using neutron radiation at Rutherford Appleton Laboratory, they still functioned well after 12 and 20 hours respectively, which is more than enough time for them in practical situations to carry out a task.

Other ongoing research by the 糖心Vlog team involves enabling robots to quickly explore a nuclear facility, and developing embedded systems that enable robots to schedule a series of tasks in real-time.

NCNR, led by the University of Birmingham, was co-funded by the research institutions, industrial collaborators and investment partners.