Models of people’s intentions and interactions will improve safety and reliability and may open new avenues for human-robot interactions and teaming. Real world settings include unprotected left turns, merging, etc.
Develop variable generative models to:
- Generate multi-agent behaviors indistinguishable from training data.
- Perform multi-agent intent inference in an unsupervised way.
- Learn teaming behaviors and adaptations.
Models will be evaluated in simulation and using real-world data.