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...
主要な著者: | Kootstra Gert, Popović Mila, Jørgensen Jimmy Alison, Kragic Danica, Petersen Henrik Gordon, Krüger Norbert |
---|---|
フォーマット: | 論文 |
言語: | English |
出版事項: |
De Gruyter
2012-06-01
|
シリーズ: | Paladyn |
主題: | |
オンライン・アクセス: | https://doi.org/10.2478/s13230-012-0020-5 |
類似資料
-
Model-Based Grasping of Unknown Objects from a Random Pile
著者:: Bruno Sauvet, 等
出版事項: (2019-09-01) -
Robotic Grasping of Unknown Objects Based on Deep Learning-Based Feature Detection
著者:: Kai Sherng Khor, 等
出版事項: (2024-07-01) -
Performance measures to benchmark the grasping, manipulation, and assembly of deformable objects typical to manufacturing applications
著者:: Kenneth Kimble, 等
出版事項: (2022-11-01) -
Imitation Learning of Whole-Body Grasps
著者:: Hsiao, Kaijen, 等
出版事項: (2005) -
An Accessible, Open-Source Dexterity Test: Evaluating the Grasping and Dexterous Manipulation Capabilities of Humans and Robots
著者:: Nathan Elangovan, 等
出版事項: (2022-04-01)