COVER STORY | ROBOTICS & REMOTE TECHNOLOGY
Above left: Remote handling manipulator used in nuclear decommissioning Photo credit: Nuclear Decommissioning Authority
Above right: The TARM long-reach boom at UKAEA’s RACE centre Photo credit: UKAEA
V Routine inspection tasks could be automated using machine learning, including the ability to detect anomalies and changes in the environment, with this information being stored in the digital twin. Relevant information can then be provided to operators or used in automated planning and control systems. LongOps will also explore how recent advances in AI and machine learning can be applied to robotic control and perception. However, machine learning relies on the availability of relevant and sufficient datasets, which do not currently exist. LongOps intends to start building these datasets.
Haptics At JET, remote handling operators rely on haptic feedback when controlling manipulators and tools, which allows them to experience the same forces and torques at the local device that are imposed on the remote device. This allows operators to ‘feel’ items which are being gripped. However, virtual simulations of haptics — which could be used for training — are currently unable to accurately recreate the feeling of manipulators interacting with the environment. Currently, operator training for haptic devices requires the use of real equipment. LongOps will explore the development of high- frequency, high-fidelity haptic simulators.
Modular software All this research will be brought together in a modular software package referred to as the prototype next- generation digital mock-up. Digital tools are often designed to be used independently, or with a limited range of interfacing modules. LongOps will make use of a modular interoperable software architecture, to promote ease of reconfiguration. This is what makes LongOps such an ambitious and
exciting programme — as well as developing new tools to improve the way operations are performed, it requires these tools to work together in a single, modular system. Different end users may require only some software
features or prioritise only some features. By managing a suite of software and basing the requirements on real-world tasks, LongOps aims to create standardised,
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modular software which can meet the various demands of nuclear decommissioning projects.
Manipulators Digital twins link the virtual world with the physical world. During 2021, LongOps placed contracts for procurement of two teleoperated manipulators. Over the next two years, LongOps will undertake
performance assessments, benchmarking tests and comparison activities within a test environment. The research programme will seek to enhance their use by using digital twin technologies, building on preliminary work on glovebox automation led by RACE as part of the UKRI-funded Robotics and AI in Nuclear Research (RAIN) academic network.
Meeting end user training needs For remote operations to be successful, the nuclear sector will need suitably qualified and experienced people. At present, training requires operators to use real hardware, which is expensive and time-consuming. Digital environments that replicate more of the operator experience offer the potential to accelerate training, increase the number of fully qualified operators and maintain and test competence over years. It will also be possible to provide better training for the diverse situations that might be experienced during real operations.
Changing nuclear decommissioning The next generation of digital tools will provide opportunities to develop decommissioning strategies, and train and conduct operations in high-consequence, constantly changing environments. RACE, UKRI, TEPCO and the NDA see digital tools and
remotely operated machines as a significant route to safer, faster, cheaper decommissioning and cost-effective future reactor design, whether it be in fusion or fission. ■
More details of the opportunities to contribute to LongOps can be found at:
https://ukaeaevents.com/longops-supplier-day
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