Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/113801
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dc.contributorDepartment of Mechanical Engineering-
dc.contributorDepartment of Industrial and Systems Engineering-
dc.creatorMa, W-
dc.creatorDuan, A-
dc.creatorLee, HY-
dc.creatorZheng, P-
dc.creatorNavarroAlarcon, D-
dc.date.accessioned2025-06-24T06:38:01Z-
dc.date.available2025-06-24T06:38:01Z-
dc.identifier.issn1551-3203-
dc.identifier.urihttp://hdl.handle.net/10397/113801-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.rightsThe following publication W. Ma, A. Duan, H. -Y. Lee, P. Zheng and D. Navarro-Alarcon, "Human-Aware Reactive Task Planning of Sequential Robotic Manipulation Tasks," in IEEE Transactions on Industrial Informatics, vol. 21, no. 4, pp. 2898-2907, April 2025 is available at https://doi.org/10.1109/TII.2024.3514130.en_US
dc.subjectAutonomy level (AL)en_US
dc.subjectHuman-robot interaction (HRI)en_US
dc.subjectReactive task planningen_US
dc.subjectSequential robotic manipulationen_US
dc.titleHuman-aware reactive task planning of sequential robotic manipulation tasksen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage2898-
dc.identifier.epage2907-
dc.identifier.volume21-
dc.identifier.issue4-
dc.identifier.doi10.1109/TII.2024.3514130-
dcterms.abstractThe recent emergence of Industry 5.0 underscores the need for increased autonomy in human-robot interaction (HRI), presenting both motivation and challenges in achieving resilient and energy-efficient production systems. To address this, in this article, we introduce a strategy for seamless collaboration between humans and robots in manufacturing and maintenance tasks. Our method enables smooth switching between temporary HRI (human-aware mode) and long-horizon automated manufacturing (fully automatic mode), effectively solving the human-robot coexistence problem. We develop a task progress monitor that decomposes complex tasks into robot-centric action sequences, further divided into three-phase subtasks. A trigger signal orchestrates mode switches based on detected human actions and their contribution to the task. In addition, we introduce a human agent coefficient matrix, computed using selected environmental features, to determine cut-points for reactive execution by each robot. To validate our approach, we conducted extensive experiments involving robotic manipulators performing representative manufacturing tasks in collaboration with humans. The results show promise for advancing HRI, offering pathways to enhancing sustainability within Industry 5.0. Our work lays the foundation for intelligent manufacturing processes in future societies, marking a pivotal step toward realizing the full potential of human-robot collaboration.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on industrial informatics, Apr. 2025, v. 21, no. 4, p. 2898-2907-
dcterms.isPartOfIEEE transactions on industrial informatics-
dcterms.issued2025-04-
dc.identifier.scopus2-s2.0-105002266887-
dc.identifier.eissn1941-0050-
dc.description.validate202506 bcch-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera3769ben_US
dc.identifier.SubFormID51006en_US
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryGreen (AAM)en_US
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