Sharing autonomy between robots and human operators could facilitate data collection of
robotic task demonstrations to continuously improve learned models. Yet, the means to …

We present a large-scale study of imitating human demonstrations on tasks that require a
virtual robot to search for objects in new environments-(1) ObjectGoal Navigation (eg'find & …

Large-scale data is an essential component of machine learning as demonstrated in recent
advances in natural language processing and computer vision research. However …

One of the advantages of teaching robots by demonstration is that it can be more intuitive for
users to demonstrate rather than describe the desired robot behavior. However, when the …

We present an assistance system that reasons about a human's intended actions during
robot teleoperation in order to provide appropriate modifications on unintended behavior …

As artificial intelligence becomes an increasingly prevalent method of enhancing robotic
capabilities, it is important to consider effective ways to train these learning pipelines and to …

We propose VRGym, a virtual reality (VR) testbed for realistic human-robot interaction.
Different from existing toolkits and VR environments, the VRGym emphasizes on building …

When humans control drones, cars, and robots, we often have some preconceived notion of
how our inputs should make the system behave. Existing approaches to teleoperation …

Teleoperation remains a dominant control paradigm for human interaction with robotic
systems. However, teleoperation can be quite challenging, especially for novice users. Even …

Open-sourced, user-friendly tools form the bedrock of scientific advancement across
disciplines. The widespread adoption of data-driven learning has led to remarkable …