activity
20182022
most citedOver-communicate no more: Situated RL agents learn concise communication protocols

2 citations · 2 across the 4 of their papers we have counts for

collaborators

6 papers

cs.MA20222 cited

Over-communicate no more: Situated RL agents learn concise communication protocols

Aleksandra Kalinowska, Elnaz Davoodi, Florian Strub +5

While it is known that communication facilitates cooperation in multi-agent settings, it is unclear how to design artificial agents that can learn to effectively and efficiently co…

cs.RO2021

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…

cs.RO2020

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…

cs.RO2019

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…

cs.RO2019

Data-Driven Gait Segmentation for Walking Assistance in a Lower-Limb Assistive Device

Aleksandra Kalinowska, Thomas A. Berrueta, Adam Zoss +1

Hybrid systems, such as bipedal walkers, are challenging to control because of discontinuities in their nonlinear dynamics. Little can be predicted about the systems' evolution wit…

cs.RO2018

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…