مورد إلكتروني
Modeling Human Motor Skills to Enhance Robots’ Physical Interaction
العنوان: | Modeling Human Motor Skills to Enhance Robots’ Physical Interaction |
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بيانات النشر: | Springer 2021 |
تفاصيل مُضافة: | Averta, Giuseppe (author) Arapi, Visar (author) Bicchi, Antonio (author) Della Santina, C. (author) Bianchi, Matteo (author) |
نوع الوثيقة: | Electronic Resource |
مستخلص: | The need for users’ safety and technology acceptability has incredibly increased with the deployment of co-bots physically interacting with humans in industrial settings, and for people assistance. A well-studied approach to meet these requirements is to ensure human-like robot motions and interactions. In this manuscript, we present a research approach that moves from the understanding of human movements and derives usefull guidelines for the planning of arm movements and the learning of skills for physical interaction of robots with the surrounding environment. Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Learning & Autonomous Control |
مصطلحات الفهرس: | Human motor control, Human-like robotic movements, Learning from humans, Machine learning, book chapter |
DOI: | 10.1007.978-3-030-71356-0_9 |
URL: | Human-Friendly Robotics 2020--978-3-030-71355-3 HFR 2020: 13th International Workshop on Human-Friendly Robotics--ba89ddba-ff3a-40a5-a0f8-c1f856126638 |
الإتاحة: | Open access content. Open access content © 2021 Giuseppe Averta, Visar Arapi, Antonio Bicchi, C. Della Santina, Matteo Bianchi |
ملاحظة: | English |
أرقام أخرى: | NLTUD oai:tudelft.nl:uuid:876bac12-26ed-4893-8ec3-6b09503ef82c doi:10.1007/978-3-030-71356-0_9 1296121092 |
المصدر المساهم: | DELFT UNIV OF TECHNOL From OAIster®, provided by the OCLC Cooperative. |
رقم الأكسشن: | edsoai.on1296121092 |
قاعدة البيانات: | OAIster |
DOI: | 10.1007.978-3-030-71356-0_9 |
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