Human facial emotion recognition for adaptive human robot collaboration in manufacturing

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dc.contributor.authorKhan, Fahad
dc.contributor.authorAsif, Seemal
dc.contributor.authorWebb, Phil
dc.date.accessioned2024-09-25T13:28:40Z
dc.date.available2024-09-25T13:28:40Z
dc.date.freetoread2024-09-25
dc.date.issued2024-08-31
dc.date.pubOnline2024-08-31
dc.description.abstractThe integration of robots into various industries, including manufacturing, has introduced new challenges in achieving efficient human-robot collaboration. A crucial aspect of successful collaboration is the ability of robots to understand and respond to human emotions. In the context of human-robot collaboration in manufacturing, accurately predicting human emotions is essential for enhancing efficiency and safety. This paper presents a setup for human emotion detection, focusing on facial emotion recognition. The proposed model and descriptive summary involve the utilising state-of-the-art algorithms such as AlexNet, HaarCascade (HCC), MTCNN (Multi-Task Cascaded Convolutional Neural Networks), and SVM (Support Vector Machine), applied to datasets like CK+, JAFFE, and AffectNet. The performance of each facial recognition model is evaluated in real-time scenarios, resulting in significant progress with an accuracy improvement from 40% to 78.1%. These results demonstrate the effectiveness of the approach in enabling adaptive robot control based on human emotions and enhancing collaboration quality. This research uniquely integrates facial emotion recognition and robot control to enable adaptive responses during human-robot collaboration in manufacturing settings. By understanding and responding to human emotions, robots can improve their interactions with humans, leading to increased productivity and improved overall collaboration efficiency.
dc.description.conferencename25th Annual Conference Towards Autonomous Robotic Systems (TAROS)
dc.description.sponsorshipThis work was supported by EPSRC-funded Made Smarter Innovation - Re-search Centre for Smart, Collaborative Industrial Robotics project (EP/V062158/1).
dc.format.extent33-47
dc.identifier.citationKhan F, Asif S, Webb P. (2024) Human facial emotion recognition for adaptive human robot collaboration in manufacturing. In: 25th Annual Conference Towards Autonomous Robotic Systems (TAROS), 21-23 August 2024, Brunel University, London. Lecture Notes in Artificial Intelligence sub series, LNCS, Volume 15052, part II, pp. 33-47
dc.identifier.eissn1611-3349
dc.identifier.elementsID553689
dc.identifier.issn0302-9743
dc.identifier.uri https://doi.org/10.1007/978-3-031-72062-8_4
dc.identifier.urihttps://taros-conference.org/2024-2/proceedings/
dc.identifier.uri https://dspace.lib.cranfield.ac.uk/handle/1826/22974
dc.identifier.volumeNo15052
dc.language.isoen
dc.publisherSpringer
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjecthuman facial recognition
dc.subjecthuman – robot collaboration
dc.subjecthuman emotion prediction
dc.subjectadaptive control
dc.subjectmachine learning
dc.titleHuman facial emotion recognition for adaptive human robot collaboration in manufacturing
dc.typeConference paper
dcterms.coverageBrunel University, London
dcterms.dateAccepted2024-06-21
dcterms.temporal.endDate23 Aug 2024
dcterms.temporal.startDate21 Aug 2024

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