Cargando…
Robust tactile object recognition in open-set scenarios using Gaussian prototype learning
Tactile object recognition is crucial for effective grasping and manipulation. Recently, it has started to attract increasing attention in robotic applications. While there are many works on tactile object recognition and they also achieved promising performances in some applications, most of them a...
Autores principales: | Zheng, Wendong, Liu, Huaping, Guo, Di, Sun, Fuchun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9832387/ https://www.ncbi.nlm.nih.gov/pubmed/36643018 http://dx.doi.org/10.3389/fnins.2022.1070645 |
Ejemplares similares
-
Open-Environment Robotic Acoustic Perception for Object Recognition
por: Jin, Shaowei, et al.
Publicado: (2019) -
Learning and recognition of tactile temporal sequences by mice and humans
por: Bale, Michael R, et al.
Publicado: (2017) -
Real-Time Occlusion-Robust Deformable Linear Object Tracking With Model-Based Gaussian Mixture Model
por: Wang, Taohan, et al.
Publicado: (2022) -
Asymmetric Functional Connectivity of the Contra- and Ipsilateral Secondary Somatosensory Cortex during Tactile Object Recognition
por: Yu, Yinghua, et al.
Publicado: (2018) -
Gradient adaptive sampling and multiple temporal scale 3D CNNs for tactile object recognition
por: Qian, Xiaoliang, et al.
Publicado: (2023)