3 papers
cs.RO2025
Contrastive Learning from Exploratory Actions: Leveraging Natural Interactions for Preference Elicitation
Nathaniel Dennler, Stefanos Nikolaidis, Maja Matarić
People have a variety of preferences for how robots behave. To understand and reason about these preferences, robots aim to learn a reward function that describes how aligned robot…
cs.RO2025
Soft and Compliant Contact-Rich Hair Manipulation and Care
Uksang Yoo, Nathaniel Dennler, Eliot Xing +4
Hair care robots can help address labor shortages in elderly care while enabling those with limited mobility to maintain their hair-related identity. We present MOE-Hair, a soft ro…
cs.RO2024
Improving User Experience in Preference-Based Optimization of Reward Functions for Assistive Robots
Nathaniel Dennler, Zhonghao Shi, Stefanos Nikolaidis +1
Assistive robots interact with humans and must adapt to different users' preferences to be effective. An easy and effective technique to learn non-expert users' preferences is thro…