4 citations · 4 across the 1 of their papers we have counts for
4 papers
Improving Robot-Centric Learning from Demonstration via Personalized Embeddings
Mariah L. Schrum, Erin Hedlund, Matthew C. Gombolay
Learning from demonstration (LfD) techniques seek to enable novice users to teach robots novel tasks in the real world. However, prior work has shown that robot-centric LfD approac…
Meta-active Learning in Probabilistically-Safe Optimization
Mariah L. Schrum, Mark Connolly, Eric Cole +3
Learning to control a safety-critical system with latent dynamics (e.g. for deep brain stimulation) requires taking calculated risks to gain information as efficiently as possible.…
Four Years in Review: Statistical Practices of Likert Scales in Human-Robot Interaction Studies
Mariah L. Schrum, Michael Johnson, Muyleng Ghuy +1
As robots become more prevalent, the importance of the field of human-robot interaction (HRI) grows accordingly. As such, we should endeavor to employ the best statistical practice…
When Your Robot Breaks: Active Learning During Plant Failure
Mariah Schrum, Matthew Gombolay
Detecting and adapting to catastrophic failures in robotic systems requires a robot to learn its new dynamics quickly and safely to best accomplish its goals. To address this chall…