HUCOM: A model for human comfort estimation in personalized human-robot collaboration

Weitian Wang, Na Liu, Rui Li, Yi Chen, Yunyi Jia

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

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.

Original languageEnglish
Title of host publicationControl 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
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791851906
DOIs
StatePublished - 2018
EventASME 2018 Dynamic Systems and Control Conference, DSCC 2018 - Atlanta, United States
Duration: 30 Sep 20183 Oct 2018

Publication series

NameASME 2018 Dynamic Systems and Control Conference, DSCC 2018
Volume2

Conference

ConferenceASME 2018 Dynamic Systems and Control Conference, DSCC 2018
Country/TerritoryUnited States
CityAtlanta
Period30/09/183/10/18

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