activity
20192022
most citedThriftyDAgger: Budget-Aware Novelty and Risk Gating for Interactive Imitation Learning

19 citations · 21 across the 4 of their papers we have counts for

collaborators

8 papers

cs.LG2022

Policy-Based Bayesian Experimental Design for Non-Differentiable Implicit Models

Vincent Lim, Ellen Novoseller, Jeffrey Ichnowski +2

For applications in healthcare, physics, energy, robotics, and many other fields, designing maximally informative experiments is valuable, particularly when experiments are expensi…

cs.RO202119 cited

ThriftyDAgger: Budget-Aware Novelty and Risk Gating for Interactive Imitation Learning

Ryan Hoque, Ashwin Balakrishna, Ellen Novoseller +3

Effective robot learning often requires online human feedback and interventions that can cost significant human time, giving rise to the central challenge in interactive imitation…

cs.RO2021

Untangling Dense Non-Planar Knots by Learning Manipulation Features and Recovery Policies

Priya Sundaresan, Jennifer Grannen, Brijen Thananjeyan +7

Robot manipulation for untangling 1D deformable structures such as ropes, cables, and wires is challenging due to their infinite dimensional configuration space, complex dynamics,…

cs.RO20212 cited

Disentangling Dense Multi-Cable Knots

Vainavi Viswanath, Jennifer Grannen, Priya Sundaresan +7

Disentangling two or more cables requires many steps to remove crossings between and within cables. We formalize the problem of disentangling multiple cables and present an algorit…

cs.RO2021

LazyDAgger: Reducing Context Switching in Interactive Imitation Learning

Ryan Hoque, Ashwin Balakrishna, Carl Putterman +6

Corrective interventions while a robot is learning to automate a task provide an intuitive method for a human supervisor to assist the robot and convey information about desired be…

cs.RO2020

Human Preference-Based Learning for High-dimensional Optimization of Exoskeleton Walking Gaits

Maegan Tucker, Myra Cheng, Ellen Novoseller +4

Optimizing lower-body exoskeleton walking gaits for user comfort requires understanding users' preferences over a high-dimensional gait parameter space. However, existing preferenc…