The nuclear industry is increasingly seeking to deploy robotic and autonomous systems were possible to reduce worker exposure to hazardous environments, improve productivity and enhance operational resilience. Whilst significant progress has been made in remote operations, a major barrier we currently still find is the ability for robots and operators to work collaboratively within the same safety envelope.
Current safety approaches generally require physical segregation, exclusion zones or reduced robot operating modes, with, in some cases, complete removal of personnel. This can limit the potential benefits we could realise with autonomy and prevents effective human-robot coexistence in complex nuclear operations.
The IISE project is aimed at developing technologies, methodologies and assurance frameworks to enable humans and robotic systems to operate safely, efficiently and collaboratively within a shared environment.
Vision
To create a nuclear working environment in which robotic systems and operators can safely coexist and collaborate within the same safety envelope, dynamically adapting to changing conditions whilst maintaining demonstrable safety and regulatory compliance.
Research Challenge
- Human behaviour is unpredictable.
- Nuclear environments are dynamic.
- Safety regulations ensure our operators face minimal risk with predictable and repeatable operations.
- Autonomous systems need to be predictable and verifiable.
- Regulatory acceptance requires demonstrable evidence of safety performance.
- The complex design of our stores make wireless communications difficult.
Research Focus Area – Digital Twin enabled Human-Robot and Sensor Collaboration
This PhD centres around the creation and management of a detailed digital twin of an environment containing human-robot interaction.
The digital twin should be a like for like representation of the area and provide real-time insights into the condition of the area, including atmosphere and temperature readings.
The digital twin should be able to detect the position and orientation of both the robot and human within the environment, and distinguish between the two in the virtual display, it would be good to explore prediction of path mapping and analysis of common routes as well to establish traffic patterns.
The system should also be able to detect and visualise potential collision points and manage these appropriately to support operator health and safety.
The digital twin should be sophisticated enough to allow for jobs to be rehearsed prior to human entry into the environment, this should be detailed to allow for as much realism as possible.
Alongside this the digital twin should be able to display the health of the sensors located within the area, providing a real time RAG status and planned maintenance requirements to ensure that components can be replaced before failure, maintaining the reliability of the digital twin as a visual representation of the real world.
Funding notes:
This position is open to UK fee payers AND international students, and the funding will cover all tuition fees and also provide a stipend to cover living costs during the student’s studies.
#J-18808-Ljbffr
PhD Studentship: PhD in an Integrated Intelligent Safe Environment (IISE) in the Nuclear Industry in Birmingham employer: University of Birmingham
The University of Birmingham is an exceptional employer, offering a vibrant academic environment that fosters innovation and collaboration. With a strong commitment to employee development, the School of Chemistry provides ample opportunities for career advancement and leadership roles, all while being situated in a dynamic city known for its rich cultural heritage and supportive community.
