AI for Robotics

We are developing algorithms to make robots learn through experience, perceive their environment, reason with knowledge, control their motion, and manipulate objects.

Our research in robot learning encompasses a large variety of topics from perceptions to behaviours.
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Our work focuses on activity analysis from video, with fundamental research on categorisation, tracking, segmentation and motion modelling, through to the application of this research in several areas. Part of the work is exploring the integration of vision within a broader cognitive framework that includes audition, language, action, and reasoning.
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Robotic manipulation refers to the ways robots interact with the objects around them: grasping an object, opening a door, packing an order into a box, folding laundry…
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We are exploring the combination of qualitative reasoning with video-based object detection and robotics to model and recognise everyday activities from the spatio-temporal relationships between people and objects.
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How do we control our behaviour, and how should we design control systems for autonomous robots? These two questions are often approached using vastly different approaches and methodologies.
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