9 citations · 9 across the 3 of their papers we have counts for
6 papers · 1 filter
Ergodic Control and Controlled Diffusion for Robot Learning: Review and Tutorial
Max Muchen Sun, Cem Bilaloglu, Ananya Rao +6
Diffusion learning leverages the statistical mechanism of diffusion processes for learning, reasoning, and inferring complex distributions from data. Recent advances in diffusion l…
Ergodic imitation: Learning from what to do and what not to do
Aleksandra Kalinowska, Ahalya Prabhakar, Kathleen Fitzsimons +1
With growing access to versatile robotics, it is beneficial for end users to be able to teach robots tasks without needing to code a control policy. One possibility is to teach the…
Dynamical System Segmentation for Information Measures in Motion
Thomas A. Berrueta, Ana Pervan, Kathleen Fitzsimons +1
Motions carry information about the underlying task being executed. Previous work in human motion analysis suggests that complex motions may result from the composition of fundamen…
Shoulder abduction loading affects motor coordination in individuals with chronic stroke, informing targeted rehabilitation
Aleksandra Kalinowska, Kyra Rudy, Millicent Schlafly +3
Individuals post stroke experience motor impairments, such as loss of independent joint control, leading to an overall reduction in arm function. Their motion becomes slower and mo…
Task-Based Hybrid Shared Control for Training Through Forceful Interaction
Kathleen Fitzsimons, Aleksandra Kalinowska, Julius P. A. Dewald +1
Despite the fact that robotic platforms can provide both consistent practice and objective assessments of users over the course of their training, there are relatively few instance…
Online User Assessment for Minimal Intervention During Task-Based Robotic Assistance
Aleksandra Kalinowska, Kathleen Fitzsimons, Julius Dewald +1
We propose a novel criterion for evaluating user input for human-robot interfaces for known tasks. We use the mode insertion gradient (MIG)---a tool from hybrid control theory---as…