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Found 5 papers, 2 papers with code
A Bayesian Framework for Nash Equilibrium Inference in Human-Robot Parallel Play
We showed that using a Bayesian approach to infer the equilibrium enables the robot to complete the task with less than half the number of collisions while also reducing the task execution time as compared to the best baseline.
Supportive Actions for Manipulation in Human-Robot Coworker Teams
We compare two robot modes in a shared table pick-and-place task: (1) Task-oriented: the robot only takes actions to further its own task objective and (2) Supportive: the robot sometimes prefers supportive actions to task-oriented ones when they reduce future goal-conflicts.
Learning to Find Common Objects Across Few Image Collections
We model the selection as an energy minimization problem with unary and pairwise potential functions.
Collaborative Planning for Mixed-Autonomy Lane Merging
Driving is a social activity: drivers often indicate their intent to change lanes via motion cues.
One-Shot Learning for Semantic Segmentation
Low-shot learning methods for image classification support learning from sparse data.
