Towards Automating the Generation of Human-Robot Interaction Scenarios

Authors

  • Matthew C. Fontaine University of Southern California

DOI:

https://doi.org/10.1609/aaai.v36i11.21575

Keywords:

Scenario Generation, Quality Diversity, Human-Robot Interaction, Generative Models, Procedural Content Generation

Abstract

My work studies the problem of generating scenarios to evaluate interaction between humans and robots. I expect these interactions to grow in complexity as robots become more intelligent and enter our daily lives. However, evaluating such interactions only through user studies, which are the de facto evaluation method in human-robot interaction, will quickly become infeasible as the number of possible scenarios grows exponentially with scenario complexity. Therefore, I propose automatically generating scenarios in simulation to explore the diverse possibility space of scenarios to better understand interaction and avoid costly failures in real world settings.

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Published

2022-06-28

How to Cite

Fontaine, M. C. (2022). Towards Automating the Generation of Human-Robot Interaction Scenarios. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12876-12877. https://doi.org/10.1609/aaai.v36i11.21575