RAD - Robust Autonomy and Decisions

A generative force model for surgical skill quantification using sensorised instruments

A. Straižys, M. Burke, P.M. Brennan, S. Ramamoorthy - Communications Engineering Vol. 2, 2023

Elaborating on learned demonstrations with temporal logic specifications

C. Innes, S. Ramamoorthy - RSS-20

Surfing on an uncertain edge: Precision cutting of soft tissue using torque-based medium classification

A. Straizys, M. Burke, S. Ramamoorthy - ICRA-20

Disentangled Relational Representations for Explaining and Learning from Demonstration

Y. Hristov, D. Angelov, A.Lascarides, M. Burke, S. Ramamoorthy - CORL-19

From explanation to synthesis: Compositional program induction for learning from demonstration

M. Burke, S. Penkov, S. Ramamoorthy - RSS-19

Robust Autonomy and Decisions Group

We investigate learning, adaptation and control mechanisms to enable autonomous robots to cope with the uncertain and the unknown. Our research focus areas include:

Dexterous manipulation skills: understanding what humans/animals do, in order to achieve similar robotic skills
Human-robot interaction, including paradigms such as machine teaching
Active sensing and incremental, compositional model learning
Physics-informed machine learning, including geometric/topological representations and multi-scale modelling
Safety and trustworthiness of autonomous systems

We develop techniques that are relevant to a broad range of applications, ranging from advanced manufacturing to mobility and field robotics. An application domain of particular current interest is healthcare technologies, including biomedical devices and biophysical discovery platforms.

Robust Autonomy and Decisions Group

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