A student working with the iCub robot

Advancing intelligent robotics for the physical, cognitive and social well-being of humans, through intelligent perception, machine learning, user modelling, cognitive control architectures, and personalised assistance generation.

Affordance-aware AR HMD UIs introduce more natural and intuitive interactions with legged manipulators by exploiting the users' existing abilities. Thus, making these interactions easier to perform and increasing the probability of acceptance by non-expert users.

A big group of robots

The diverse capabilities required for assistive robotics applications such as mobility assistance, household maintenance and meal preparation are difficult, if not impossible, to build into a single robot. Therefore, these capabilities must be distributed among different robot types.

Assistive robots can support people with disabilities in a variety of activities of daily living such as dressing. People who have completely lost their upper limb movement functionality may benefit from robot-assisted dressing, which involves complex deformable garment manipulation.

Personal Robotics Laboratory Multi-Robot Affordances Augmented Reality

In our laboratory, we investigate how head-mounted augmented reality interfaces for assistive human-robot interaction transfer onto multirobot architectures. Several assistive robotics applications need to be distributed among robots that are different both physically and in terms of software.

Lab overview

In the Personal Robotics Lab, we perform research towards intelligent robotic devices that are capable of interacting with their users, learning from this interaction, as well as adapting the assistance provided in order to maximise their users' physical, cognitive and social well-being. Our research spans several topic areas, including machine learning, user modelling, cognitive architectures, human action analysis and shared control. We are aiming at advancing fundamental theoretical concepts in these fields, but without ignoring the engineering challenges of the real world, so our experiments involve real robots, real humans and real tasks.

Our research is of a highly experimental nature and is internationally well recognised through accepted papers at major conferences, renowned scientific journals and frequently invited presentations.