2022 AAAI AAAI 2022

Towards Automating the Generation of Human-Robot Interaction Scenarios

Abstract

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.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Computer Science and Machine Learning and Robotics
📈 Trend Setter — Human-Robot Interaction
🐣 Hot Topic Early Bird — autonomous agent
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio