Research project

User-aware adaptive human-robot interaction

Project overview

This project investigates how social and collaborative robots can adapt their behaviour to individual users during human–robot interaction. Rather than assuming that all users have the same preferences, tolerances and interaction styles, the research develops user-aware decision-making frameworks that learn from both explicit feedback and implicit behavioural signals.

The work combines online learning and constrained decision making with multimodal sensing of human behaviour, including facial expression, body pose and verbal interaction. A particular focus is understanding and reducing user frustration while enabling robots to learn individual preferences and provide effective assistance.

The research has been evaluated through human–robot interaction studies involving TIAGo and Pepper robots across collaborative manipulation, assistive localisation and social interaction scenarios. The broader aim is to develop autonomous robots that adapt their behaviour during interaction in response to the needs and reactions of individual users.

Staff

Lead researchers

Dr Danesh Tarapore

Associate Professor
Research interests
  • Resilient autonomy
  • Field robotics
  • Swarm and multi-robot systems
Connect with Danesh

Other researchers

Dr Tan Viet Tuyen Nguyen

New Frontiers Fellow
Research interests
  • Human-centered Artificial Intelligence
  • Social Human-Robot Interaction
  • Multimodal Perception and Interaction
Connect with Tan Viet Tuyen

Professor Bing Chu

Professor
Connect with Bing

Collaborating research institutes, centres and groups

Research outputs