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Grasp Detection for Robot to Human Handovers Using Capacitive Sensors

Mamaev, Ilshat; Kretsch, David; Alagi, Hosam ORCID iD icon; Hein, Björn

Abstract:

As it happens, despite yet unmatched by robots perception and motor skills humans drop objects during handover because of false grasp detection and early release. Accordingly, the fluent robot-human handover is still an open challenge. This paper presents an approach to a natural robot to human handover using Capacitive Proximity Sensor (CPS) for robust grasp detection and release trigger. We propose an experimental setup for the evaluation using a collaborative robot, an eye-in-hand depth camera, and CPS integrated into the gripper. Three grasp detection methods were implemented and an object release was triggered based on torque-sensing, capacitive sensing, and the combination of both. Finally, a user study was designed and conducted, indicating that the capacitive method is the most preferred type with the shortest human idle time and the highest fluency ratings.

Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Fakultät für Informatik – Institut für Prozessrechentechnik, Automation und Robotik (IPR)
Publikationstyp Proceedingsbeitrag
Publikationsmonat/-jahr 05.2021
Sprache Englisch
Identifikator ISBN: 978-1-7281-9078-5
KITopen-ID: 1000139218
Erschienen in 2021 IEEE International Conference on Robotics and Automation (ICRA), Xi'an, China, 30 May-5 June 2021
Veranstaltung IEEE International Conference on Robotics and Automation (ICRA 2021), Xi'an, China, 30.05.2021 – 05.06.2021
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 12552–12558
Nachgewiesen in Scopus
Dimensions
OpenAlex
Globale Ziele für nachhaltige Entwicklung Ziel 4 – Hochwertige BildungZiel 9 – Industrie, Innovation und Infrastruktur

Originalveröffentlichung
DOI: 10.1109/ICRA48506.2021.9560970
Scopus
Zitationen: 8
Dimensions
Zitationen: 9
Seitenaufrufe: 141
seit 21.10.2021
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