Machine Learning for Predicting User Satisfaction in Human–Robot Interaction (HRI) Teleoperation Tasks

Predicting user satisfaction in Human–Robot Interaction (HRI) tasks is essential to enhancing system adaptability and user experience. This study addresses this challenge in the context of teleoperated Autonomous Ground Vehicles (AGVs) by introducing the Robot Motion Dataset (RMD). This multi...

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Hlavní autoři:	Antonio Di Tecco, Antonio Frisoli, Claudio Loconsole
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2025-01-01
Edice:	IEEE Access
Témata:	Artificial intelligence collision avoidance cybernetics data analysis database human–robot interaction (HRI)
On-line přístup:	https://ieeexplore.ieee.org/document/11122863/
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