Cargando…
Enhancing Human–Robot Collaboration through a Multi-Module Interaction Framework with Sensor Fusion: Object Recognition, Verbal Communication, User of Interest Detection, Gesture and Gaze Recognition
With the increasing presence of robots in our daily lives, it is crucial to design interaction interfaces that are natural, easy to use and meaningful for robotic tasks. This is important not only to enhance the user experience but also to increase the task reliability by providing supplementary inf...
Autores principales: | Paul, Shuvo Kumar, Nicolescu, Mircea, Nicolescu, Monica |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10347030/ https://www.ncbi.nlm.nih.gov/pubmed/37447647 http://dx.doi.org/10.3390/s23135798 |
Ejemplares similares
-
Gaze Gesture Recognition by Graph Convolutional Networks
por: Shi, Lei, et al.
Publicado: (2021) -
User-Independent Hand Gesture Recognition Classification Models Using Sensor Fusion
por: Colli Alfaro, Jose Guillermo, et al.
Publicado: (2022) -
Gesture recognition
por: Coleman, Gilberto
Publicado: (2018) -
Gesture recognition
por: Escalera, Sergio, et al.
Publicado: (2017) -
A touch-free human-robot collaborative surgical navigation robotic system based on hand gesture recognition
por: Wang, Jie, et al.
Publicado: (2023)