7 accepted papers
Large language models (LLMs) are increasingly used in robotics, especially for high-level action planning. Meanwhile, many robotics applications involve human supervisors or collaborators. Hence, it is crucial for LLMs to generate socially acceptable actions that align with people’s preferences and…
"Hey, robot. Let’s tidy up the kitchen. By the way, I have back pain today". How can a robotic system devise a shared plan with an appropriate task allocation from this abstract goal and agent condition? Classical AI task planning has been explored for this purpose, but it involves a tedious definit…
Modern robots need to adapt to diverse human partners with whom they collaborate. To this end, learning a representation of human capabilities enables the robot to personalize their behaviour to their collaborators across multiple tasks. We propose CApability Modeling from Observations (CAMO), a mod…
Human-Robot Collaboration (HRC) has become a major trend in robotics in recent years with the idea of combining the strengths from both humans and robots. In order to share the work to be done, many task planning approaches have been implemented. However, they don't fully satisfy the required adapta…
For users to trust planning algorithms, they must be able to understand the planner's outputs and the reasons for each action selection. This output does not tend to be user-friendly, often consisting of sequences of parametrised actions or task networks. And these may not be practical for non-exper…
Recent research in AI ethics has put forth explainability as an essential principle for AI algorithms. However, it is still unclear how this is to be implemented in practice for specific classes of algorithms—such as motion planners. In this paper we unpack the concept of explanation in the context…
For a safe and successful daily living assistance, far from the highly controlled environment of a factory, robots should be able to adapt to ever-changing situations. Programming such a robot is a tedious process that requires expert knowledge. An alternative is to rely on a high-level planner, but…