Grasp Detection under Occlusions Using SIFT Features
Distinguishing target object under occlusions has become the forefront of research to cope with grasping study in general. In this paper, a novel framework which is able to be utilized for a parallel robotic gripper is proposed. There are two key steps for the proposed method in the process of grasp...
Guardado en:
Autores principales: | Zhaojun Ye, Yi Guo, Chengguang Wang, Haohui Huang, Genke Yang |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Hindawi-Wiley
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/439dd8e048c34989a9bd477f043ed4dc |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Grasp detection via visual rotation object detection and point cloud spatial feature scoring
por: Jie Wang, et al.
Publicado: (2021) -
Planning for grasping cluttered objects based on obstruction degree
por: Wenrui Zhao, et al.
Publicado: (2021) -
Feature fusion-based collaborative learning for knowledge distillation
por: Yiting Li, et al.
Publicado: (2021) -
Cooperative Cloud-Edge Feature Extraction Architecture for Mobile Image Retrieval
por: Chao He, et al.
Publicado: (2021) -
Genomic features of Mycobacterium avium subsp. hominissuis isolated from pigs in Japan
por: Tetsuya Komatsu, et al.
Publicado: (2021)