Name
Abstract | ||
|---|---|---|
Grasping is a complex process involving knowledge of the object, the surroundings, and of oneself. While humans are able to integrate and process all of the sensory information required for performing this task, equipping machines with this capability is an extremely challenging endeavor. In this paper, we investigate how deep learning techniques can allow us to translate high-level concepts such ... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/LRA.2017.2651945 | IEEE Robotics and Automation Letters |
Keywords | DocType | Volume |
Grasping,Robot sensing systems,Machine learning,Encoding,Visualization,Generators | Journal | 2 |
Issue | ISSN | Citations |
2 | 2377-3766 | 4 |
PageRank | References | Authors |
0.45 | 11 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matthew Veres | 1 | 14 | 1.69 |
| M. A. Moussa | 2 | 43 | 3.47 |
| Graham W. Taylor | 3 | 1523 | 127.22 |