Human-Centered Optimization of Task Allocation in Multi Human-Robot Systems

dc.contributor.author	Safari Dehnavi, Zahra
dc.contributor.author	Schlund, Sebastian
dc.date.accessioned	2023-08-24T06:24:30Z
dc.date.available	2023-08-24T06:24:30Z
dc.date.issued	2023
dc.description.abstract	In industrial settings, multi-human-robot systems are common. Enhancing work systems requires considering human factors in task allocation between humans and robots. This paper highlights the significance of human-centric task allocation in multi agent settings. The research tackles three challenges in optimized task allocation: complex optimization models with machine learning algorithms, accurate representation of human factors, and effective human-robot interfaces. Overcoming these challenges is vital for improving productivity and well-being of human workers.	de
dc.identifier.doi	10.18420/muc2023-mci-ws16-398
dc.identifier.uri	https://dl.gi.de/handle/20.500.12116/42147
dc.publisher	GI
dc.relation.ispartof	Mensch und Computer 2023 - Workshopband
dc.relation.ispartofseries	Mensch und Computer
dc.subject	Task allocation
dc.subject	Multi-human-robot task sharing
dc.subject	AI
dc.subject	human-centered
dc.title	Human-Centered Optimization of Task Allocation in Multi Human-Robot Systems	de
dc.type	Text/Workshop Paper
gi.conference.date	3.-6. September 2023
gi.conference.location	Rapperswil
gi.conference.sessiontitle	MCI-WS16 - UCAI 2023: Workshop on User-Centered Artificial Intelligence

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