Robot Perception through Wearable Sensors: Decoding Grasping for Human-Robot Hand-Over

التفاصيل البيبلوغرافية
العنوان: Robot Perception through Wearable Sensors: Decoding Grasping for Human-Robot Hand-Over
المؤلفون: Bonci, Andrea, Burattini, Laura, Fioretti, Sandro, Giannini, Maria Cristina, Longhi, Sauro, Mengarelli, Alessandro, Tigrini, Andrea, Verdini, Federica
سنة النشر: 2022
المجموعة: Zenodo
مصطلحات موضوعية: Human-Robot interaction, Hand-Over, Pattern recognition, Myoelectric signal, Grasping
الوصف: Human-robot interaction represents the cornerstone for the full development of Industry 4.0 and 5.0 paradigms, that rely on this cooperation in order to develop more efficient and flexible production lines. In this context, the human-robot handover plays a crucial role and many approaches were introduced to plan and control this task, including the less investigated decoding of human muscles activity. Hence, the design of reliable myoelectric human-robot interfaces is a point of primary interest. This paper investigates the use of a wearable device, i.e. an armband, for achieving a robust detection of several human grasping gestures. An evaluation of the most useful features, belonging to three different computational domains, is also proposed. Outcomes showed that high recognition performance can be achieved with limited computational burden, which is crucial when dealing with real-time demands in collaborative task.
نوع الوثيقة: conference object
اللغة: unknown
العلاقة: https://zenodo.org/communities/irim-2022Test; https://zenodo.org/record/7531374Test; https://doi.org/10.5281/zenodo.7531374Test; oai:zenodo.org:7531374
DOI: 10.5281/zenodo.7531374
الإتاحة: https://doi.org/10.5281/zenodo.7531374Test
https://doi.org/10.5281/zenodo.7531373Test
https://zenodo.org/record/7531374Test
حقوق: info:eu-repo/semantics/openAccess ; https://creativecommons.org/licenses/by/4.0/legalcodeTest
رقم الانضمام: edsbas.50A85E1A
قاعدة البيانات: BASE