Work

Human-in-the-loop testing of the explainability of robot navigation algorithms in extended reality

Year: 2024

Type: conference-paper

Abstract: Developing robots to be deployed in spaces shared with people requires testing with humans-in-the-loop. In fact, only humans co-located with the robots are in a suitable position to judge the robots’ behaviors. This is especially important when people participate in the same task as the robots, like when navigating a shared environment: the actions of people and robots influence each other. To test the resulting dynamic system, we need to let real people experience the interaction, which, when done in simulation, translates to immersing real users using Virtual or Mixed Reality. We implement and demonstrate this solution where users experience variable legibility, predictability, and explainability of the robot navigation algorithms, depending on if and how the robots explicitly communicate their intentions.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.14864852

Authors: Guzzi, Jérôme, Giusti, Alessandro

Institution: Dalle Molle Institute for Artificial Intelligence Research

Language: English

Topic: Explainable Artificial Intelligence (XAI)

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: European Commission, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Awards: Fortsetzung der Lesung und Interpretation griechischer Papyrusurkunden aus der Sammlung Erzherzog Rainer in Wien, REliable & eXplAinable Swarm Intelligence for People with Reduced mObility