Human Aspects in Collaborative Order Picking – What if Robots Learned How to Give Humans a Break?

Yaxu Niu, Frederik Schulte*

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

Human aspects in collaboration of humans and robots, as common in warehousing, are considered increasingly important objectives in operations management. In this work, we let robots learn about human stress levels based on sensor data in collaborative order picking of robotic mobile fulfillment systems. To this end, we develop a multi-agent reinforcement (MARL) approach that considers human stress levels and recovery behavior next to traditional performance objectives in the reward function of robotic agents. We assume a human-oriented assignment problem in which the robotic agents assign orders and short breaks to human workers based on their stress/recovery states. We find that the proposed MARL policy reduces the human stress time by up 50% in comparison to the applied benchmark policies and maintains system efficiency at a comparable level. While the results may need to be confirmed in different settings considering different types of humans aspects and efficiency objectives, they also show a practicable pathway to control stress levels and recovery for related problems of human-robot collaboration, inside and outside of warehousing.

Original languageEnglish
Title of host publicationProceedings IFIP International Conference on Advances in Production Management Systems
EditorsAlexandre Dolgui, Alain Bernard, David Lemoine, Gregor von Cieminski, David Romero
PublisherSpringer
Pages541-550
ISBN (Electronic)978-3-030-85906-0
ISBN (Print)978-3-030-85905-3
DOIs
Publication statusPublished - 2021
EventIFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2021 - Nantes, France
Duration: 5 Sep 20219 Sep 2021

Publication series

NameIFIP Advances in Information and Communication Technology
Volume632 IFIP
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X

Conference

ConferenceIFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2021
CountryFrance
CityNantes
Period5/09/219/09/21

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care

Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Human aspects
  • Human-robot collaboration
  • Multi-agent reinforcement learning
  • Order picking
  • Recovery
  • Robotic mobile fulfillment systems
  • Sensor data

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