VisGraB: A Benchmark for Vision-Based Grasping
We present a database and a software tool, VisGraB, for benchmarking of methods for vision-based grasping of unknown objects with no prior object knowledge. The benchmark is a combined real-world and simulated experimental setup. Stereo images of real scenes containing several objects in different c...
Main Authors: | Kootstra Gert, Popović Mila, Jørgensen Jimmy Alison, Kragic Danica, Petersen Henrik Gordon, Krüger Norbert |
---|---|
格式: | 文件 |
语言: | English |
出版: |
De Gruyter
2012-06-01
|
丛编: | Paladyn |
主题: | |
在线阅读: | https://doi.org/10.2478/s13230-012-0020-5 |
相似书籍
-
Model-Based Grasping of Unknown Objects from a Random Pile
由: Bruno Sauvet, et al.
出版: (2019-09-01) -
Robotic Grasping of Unknown Objects Based on Deep Learning-Based Feature Detection
由: Kai Sherng Khor, et al.
出版: (2024-07-01) -
Performance measures to benchmark the grasping, manipulation, and assembly of deformable objects typical to manufacturing applications
由: Kenneth Kimble, et al.
出版: (2022-11-01) -
Imitation Learning of Whole-Body Grasps
由: Hsiao, Kaijen, et al.
出版: (2005) -
An Accessible, Open-Source Dexterity Test: Evaluating the Grasping and Dexterous Manipulation Capabilities of Humans and Robots
由: Nathan Elangovan, et al.
出版: (2022-04-01)