11 citations · 32 across the 12 of their papers we have counts for
10 papers · 1 filter
Verifiably Following Complex Robot Instructions with Foundation Models
Benedict Quartey, Eric Rosen, Stefanie Tellex +1
When instructing robots, users want to flexibly express constraints, refer to arbitrary landmarks, and verify robot behavior, while robots must disambiguate instructions into speci…
Language-Conditioned Observation Models for Visual Object Search
Thao Nguyen, Vladislav Hrosinkov, Eric Rosen +1
Object search is a challenging task because when given complex language descriptions (e.g., "find the white cup on the table"), the robot must move its camera through the environme…
A Virtual Reality Teleoperation Interface for Industrial Robot Manipulators
Eric Rosen, Devesh K. Jha
We address the problem of teleoperating an industrial robot manipulator via a commercially available Virtual Reality (VR) interface. Previous works on VR teleoperation for robot ma…
LTL-Transfer: Skill Transfer for Temporal Task Specification
Jason Xinyu Liu, Ankit Shah, Eric Rosen +3
Deploying robots in real-world environments, such as households and manufacturing lines, requires generalization across novel task specifications without violating safety constrain…
Learning robot motor skills with mixed reality
Eric Rosen, Sreehari Rammohan, Devesh Jha
Mixed Reality (MR) has recently shown great success as an intuitive interface for enabling end-users to teach robots. Related works have used MR interfaces to communicate robot int…
A Tool for Organizing Key Characteristics of Virtual, Augmented, and Mixed Reality for Human-Robot Interaction Systems: Synthesizing VAM-HRI Trends and Takeaways
Thomas R. Groechel, Michael E. Walker, Christine T. Chang +2
Frameworks have begun to emerge to categorize Virtual, Augmented, and Mixed Reality (VAM) technologies that provide immersive, intuitive interfaces to facilitate Human-Robot Intera…
Value-Based Reinforcement Learning for Continuous Control Robotic Manipulation in Multi-Task Sparse Reward Settings
Sreehari Rammohan, Shangqun Yu, Bowen He +4
Learning continuous control in high-dimensional sparse reward settings, such as robotic manipulation, is a challenging problem due to the number of samples often required to obtain…
Bootstrapping Motor Skill Learning with Motion Planning
Ben Abbatematteo, Eric Rosen, Stefanie Tellex +1
Learning a robot motor skill from scratch is impractically slow; so much so that in practice, learning must be bootstrapped using a good skill policy obtained from human demonstrat…
Steps Towards Best Practices For Robot Videos
Eric Rosen, Stefanie Tellex, Geroge Konidaris
There are unwritten guidelines for how to make robot videos that researchers learn from their advisors and pass onto their students. We believe that it is important for the communi…
Communicating Robot Arm Motion Intent Through Mixed Reality Head-mounted Displays
Eric Rosen, David Whitney, Elizabeth Phillips +4
Efficient motion intent communication is necessary for safe and collaborative work environments with collocated humans and robots. Humans efficiently communicate their motion inten…