We develop a taxonomy that categorizes HRI failure types and their impact on trust to
structure the broad range of knowledge contributions. We further identify research gaps in …

We consider robot learning in the context of shared autonomy, where control of the system
can switch between a human teleoperator and autonomous control. In this setting we …

We consider shared autonomy systems where multiple operators (AI and human), can
interact with the environment, eg by controlling a robot. The decision problem for the shared …

Recent successes combine reinforcement learning algorithms and deep neural networks,
despite reinforcement learning not being widely applied to robotics and real world …

Given the complexity of real-world, unstructured domains, it is often impossible or impractical
to design models that include every feature needed to handle all possible scenarios that an …

Many sequential decision-making problems that are currently automated, such as those in
manufacturing or recommender systems, operate in an environment where there is either …

Long-term autonomous robotic systems in highly dynamic real-world applications are
becoming a reality. Nonetheless, ensuring a certain level of robustness for these systems is …

The use of robots in educational and STEM engagement activities is widespread. In this
paper we describe a system developed for engaging learners with the design of dialogue …

Autonomous systems have a long history in the fields of Artificial Intelligence (AI) and
Robotics. However, only through recent advances in technology has it been possible to …

This project proposes a framework for online adaptation of robot behaviours deployed
autonomously in social settings with the goal of increasing the overall users' engagement …