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20172022
most citedBootstrapping Motor Skill Learning with Motion Planning

1 citations · 2 across the 5 of their papers we have counts for

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5 papers · 1 filter

cs.RO2022

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…

cs.RO20211 cited

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…

cs.RO20211 cited

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…

cs.RO2020

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…

cs.RO2017

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…