Towards a Cognitive Framework for Multimodal Person Recognition in Multiparty HRI
| Autor: | Giulio Sandini, Alessandra Sciutti, Rea Francesco, Jonas Gonzalez, Giulia Belgiovine |
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| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Cognitive framework Computer science Process (engineering) 02 engineering and technology Multimodality Multiparty human-robot interaction Person recognition Parameter identification problem 020901 industrial engineering & automation Social skills Human–computer interaction 0202 electrical engineering electronic engineering information engineering Robot 020201 artificial intelligence & image processing |
| Zdroj: | HAI |
| Popis: | The ability to recognize human partners is an important social skill to build personalized and long-term Human-Robot Interactions (HRI). However, in HRI contexts, unfolding in ever-changing and realistic environments, the identification problem presents still significant challenges. Possible solutions consist of relying on a multimodal approach and making robots learn from their first-hand sensory data. To this aim, we propose a framework to allow robots to autonomously organize their sensory experience into a structured dataset suitable for person recognition during a multiparty interaction. Our results demonstrate the effectiveness of our approach and show that it is a promising solution in the quest of making robots more autonomous in their learning process. |
| Databáze: | OpenAIRE |
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