The National Robotarium is home to a diverse range of expertise in robotics and Artificial Intelligence.
Researchers from Heriot-Watt University and The University of Edinburgh work across the following themes:
Bio-inspired robotics involves studying biological systems found in nature and applying their principles to create robots that can mimic their movements and behaviours. By learning from nature, bio-inspired robots can be designed to be more versatile and efficient.
For robots to be able to safely operate and interact in different environments, they must be able to see and understand the world around them. Our experts are advancing 2D and 3D vision and perception technologies to equip robots with the data visualisation and processing power to complete complex tasks and navigate through unstructured environments.
Robotics has the potential to revolutionise the delivery of healthcare. From patient monitoring and diagnostics to rehabilitation and robotic surgery, robots can ease staff workloads, prevent infection control and improve patient care. Our research in healthcare robotics isn’t purely theoretical; we work directly with patients, clinicians and other healthcare professionals to ensure robotic and AI technologies address real-world challenges in the sector.
Generative AI is revolutionising the field of robotics by combining vision, language, and robot actions in new systems which can learn from data, interact with humans and the world, and adapt to new situations.
Generative models such as LLMs (large language models) and VLMs (vision and language models) are now being extended for use in robotics, allowing robots to become more adaptable, intelligent, and capable of performing a wider range of real-world tasks. This technology has the potential to transform industries such as manufacturing, healthcare, and logistics.
Developing robots with logical reasoning, problem-solving and planning abilities enables them to approach and complete tasks of greater complexity, with greater autonomy. Robotic reasoning, control and learning skills enhance the interactions between humans and robots, making them more intuitive and better able to respond effectively to commands. These capabilities also enable robots to continuously improve their performance based on learning and adaptation through different scenarios.
Field robotics involves deploying robots in unstructured and dynamic environments such as agriculture, construction, the marine environment, mining, environmental monitoring, and search and rescue. These robots use advanced sensors and AI to navigate and perform tasks autonomously, improving efficiency and safety.
Field robotics is transforming industries by enhancing productivity and sustainability.
Robotics control for the real world involves developing systems that enable robots to perceive, plan, and execute actions effectively in dynamic and unstructured environments.
Intelligent control systems manage interactions between robots and their environments, ensuring precise performance, while augmented reality enhances control through interactive, real-time interfaces. These advancements make robots more adaptable and efficient in real-world applications.
Significant advances in Machine Learning have led to its ubiquitous deployment in autonomous systems. However, Machine Learning is a black-box technology meaning that any system that adopts it could potentially compromise safety, security, and interoperability.
The SAIR research theme is focused on building safer and more secure machine-learning components, ensuring that robotics and AI are developed to work within society in a responsible, verifiable, ethical, legal and safe manner.
Research in this area will align with international regulatory functions such as the EU AI Act and The Bletchley Park AI Declaration.
If you’re interested in speaking with us about our research, contact our academic co-leads:
Heriot-Watt University
Edinburgh, Scotland
UK EH14 4AS
Scottish registered charity number SC000278
The University of Edinburgh
Edinburgh, Scotland
EH8 9YL
Scottish registered charity number SC005336
