We review the idea that Theory of Mind—our ability to reason about other people's mental
states—can be formalized as inverse reinforcement learning. Under this framework …

Robots are becoming increasingly omnipresent in our daily lives, supporting us and carrying
out autonomous tasks. In Human-Robot Interaction, human actors benefit from …

For an autonomous system to be helpful to humans and to pose no unwarranted risks, it
needs to align its values with those of the humans in its environment in such a way that its …

Most motion in robotics is purely functional, planned to achieve the goal and avoid
collisions. Such motion is great in isolation, but collaboration affords a human who is …

In shared autonomy, a user and autonomous system work together to achieve shared goals.
To collaborate effectively, the autonomous system must know the user's goal. As such, most …

In this paper we present a framework that allows a human and a robot to perform
simultaneous manipulation tasks safely in close proximity. The proposed framework is …

There has been significant interest of late in generating behavior of agents that is
interpretable to the human (observer) in the loop. However, the work in this area has …

Objective: The objective of this work was to examine human response to motion-level robot
adaptation to determine its effect on team fluency, human satisfaction, and perceived safety …

Adaptation is critical for effective team collaboration. This paper introduces a computational
formalism for mutual adaptation between a robot and a human in collaborative tasks. We …

Intelligent robots and machines are becoming pervasive in human populated environments.
A desirable capability of these agents is to respond to goal-oriented commands by …