activity
20222024
most citedA metric for characterizing the arm nonuse workspace in poststroke individuals using a robot arm

8 citations · 16 across the 11 of their papers we have counts for

collaborators

11 papers

cs.RO2024

Quality Diversity for Robot Learning: Limitations and Future Directions

Sumeet Batra, Bryon Tjanaka, Stefanos Nikolaidis +1

Quality Diversity (QD) has shown great success in discovering high-performing, diverse policies for robot skill learning. While current benchmarks have led to the development of po…

cs.RO2024

Using Causal Trees to Estimate Personalized Task Difficulty in Post-Stroke Individuals

Nathaniel Dennler, Stefanos Nikolaidis, Maja Matarić

Adaptive training programs are crucial for recovery post stroke. However, developing programs that automatically adapt depends on quantifying how difficult a task is for a specific…

cs.RO2024

Singing the Body Electric: The Impact of Robot Embodiment on User Expectations

Nathaniel Dennler, Stefanos Nikolaidis, Maja Matarić

Users develop mental models of robots to conceptualize what kind of interactions they can have with those robots. The conceptualizations are often formed before interactions with t…

cs.RO20248 cited

A metric for characterizing the arm nonuse workspace in poststroke individuals using a robot arm

Nathaniel Dennler, Amelia Cain, Erica De Guzman +4

An over-reliance on the less-affected limb for functional tasks at the expense of the paretic limb and in spite of recovered capacity is an often-observed phenomenon in survivors o…

cs.RO2024

The RoSiD Tool: Empowering Users to Design Multimodal Signals for Human-Robot Collaboration

Nathaniel Dennler, David Delgado, Daniel Zeng +2

Robots that cooperate with humans must be effective at communicating with them. However, people have varied preferences for communication based on many contextual factors, such as…

cs.RO2023

Signal Temporal Logic-Guided Apprenticeship Learning

Aniruddh G. Puranic, Jyotirmoy V. Deshmukh, Stefanos Nikolaidis

Apprenticeship learning crucially depends on effectively learning rewards, and hence control policies from user demonstrations. Of particular difficulty is the setting where the de…