Workshop Program

09:00 – 10:00Welcoming + Invited Talk “Making Robots Explainable and Trustworthy” by Lars KunzePhilipp Cimiano
10:00 – 10:25Towards Improving Large Language Models’ Planning Capabilities on WoT Thing Descriptions by Generating Python Objects as Intermediary RepresentationsLukas Kinder & Tobias Käfer
10:25 – 10:55Coffee break
10:55 – 11:20Mixing Mastery: Bridging Human Knowledge to Domestic RoboticsVanessa Hassouna, Alina Hawkin & Michael Beetz
11:20 – 11:45The SPA Ontology: Towards a Web of Things Ready for Robotic AgentsMichael Freund, Daniel Schraudner, Sebastian Schmid, Christoph Stade, Thomas Wehr & Andreas Harth
11:45 – 12:10Towards a Knowledge Engineering Methodology for Flexible Robot Manipulation in Everyday TasksMichaela Kümpel, Jan-Philipp Töberg, Vanessa Hassouna, Philipp Cimiano & Michael Beetz
12:10 – 12:20Towards Seamless Human-Robot Dialogue through a Robot Action OntologyDiego Reforgiato Recupero & Lorenzo Boi
12:20 – 12:30KB4RL: Towards a Knowledge Base for automatic creation of State and Action Spaces for Reinforcement LearningLobna Joualy, Eric Demeester & Nikolaos Tsiogkas

Invited Talk: Making Robots Explainable and Trustworthy
Autonomous robot systems operating in real-world environments are required to understand their surroundings, assess their capabilities, and explain what they have seen, what they have done, what they planning to do, and why. These explanations need to be tailored to different stakeholders including end-users, developers, and regulators. In this talk, I will discuss how we design, develop, and evaluate fundamental AI technologies in simulation and real-world applications to make robots explainable and trustworthy and how this helps to overcome critical barriers which impede the current deployment of autonomous systems in economically and socially important areas.