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Active collision avoidance for human-robot collaboration driven by vision sensors
Department of Production Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.
Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID-id: 0000-0002-8906-630X
Department of Production Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.
2017 (Engelska)Ingår i: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 30, nr 9, s. 970-980Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Establishing safe human-robot collaboration is an essential factor for improving efficiency and flexibility in today's manufacturing environment. Targeting safety in human-robot collaboration, this paper reports a novel approach for effective online collision avoidance in an augmented environment, where virtual three-dimensional (3D) models of robots and real images of human operators from depth cameras are used for monitoring and collision detection. A prototype system is developed and linked to industrial robot controllers for adaptive robot control, without the need of programming by the operators. The result of collision detection reveals four safety strategies: the system can alert an operator, stop a robot, move away the robot, or modify the robot's trajectory away from an approaching operator. These strategies can be activated based on the operator's existence and location with respect to the robot. The case study of the research further discusses the possibility of implementing the developed method in realistic applications, for example, collaboration between robots and humans in an assembly line.

Ort, förlag, år, upplaga, sidor
Taylor & Francis, 2017. Vol. 30, nr 9, s. 970-980
Nyckelord [en]
collision detection, collaborative assembly, safety, vision sensor
Nationell ämneskategori
Robotteknik och automation
Forskningsämne
Produktion och automatiseringsteknik; INF201 Virtual Production Development
Identifikatorer
URN: urn:nbn:se:his:diva-13825DOI: 10.1080/0951192X.2016.1268269ISI: 000402991300006Scopus ID: 2-s2.0-85006100717OAI: oai:DiVA.org:his-13825DiVA, id: diva2:1113661
Tillgänglig från: 2017-06-22 Skapad: 2017-06-22 Senast uppdaterad: 2019-01-24Bibliografiskt granskad

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Schmidt, Bernard

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