@inproceedings{2b523413ce414ffc8ae9469cc90fbdbc,
title = "HUCOM: A model for human comfort estimation in personalized human-robot collaboration",
abstract = "Human comfort is significant in human-robot collaboration since it can influence the task efficiency and quality. In this paper, we propose a computational Human Comfort Model (HuCoM) to model and quantify the human comfort during human-robot collaborative manufacturing. Based on the defined primitive comfort rewards and combined comfort rewards, the HuCoM is developed with an incorporation of the static comfort model and the dynamic comfort model. We validate and evaluate the proposed model by several human-robot collaborative tasks via a YuMi robot.",
author = "Weitian Wang and Na Liu and Rui Li and Yi Chen and Yunyi Jia",
note = "Funding Information: This work was supported in part by the National Science Foundation Grant CRII-1755771 and a subaward from the ARM Institute (W911NF-17-3-0004). Publisher Copyright: Copyright {\textcopyright} 2018 ASME; null ; Conference date: 30-09-2018 Through 03-10-2018",
year = "2018",
doi = "10.1115/DSCC2018-9245",
language = "English",
series = "ASME 2018 Dynamic Systems and Control Conference, DSCC 2018",
publisher = "American Society of Mechanical Engineers (ASME)",
booktitle = "Control and Optimization of Connected and Automated Ground Vehicles; Dynamic Systems and Control Education; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Energy Systems; Estimation and Identification; Intelligent Transportation and Vehicles; Manufacturing; Mechatronics; Modeling and Control of IC Engines and Aftertreatment Systems; Modeling and Control of IC Engines and Powertrain Systems; Modeling and Management of Power Systems",
}