Name
Abstract | ||
|---|---|---|
Acquiring new knowledge through interactive learning mechanisms is a key ability for humanoid robots in a natural environment. Such learning mechanisms need to be performed autonomously, and through interaction with the environment or with other agents/humans. In this paper, we describe a dialogue approach and a dynamic object model for learning semantic categories, object descriptions, and new words acquisition for object learning and integration with visual perception for grounding objects in the real world. The presented system has been implemented and evaluated on the humanoid robot Armar III. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.robot.2008.08.012 | Robotics and Autonomous Systems |
Keywords | Field | DocType |
Dialogue management,Learning,Knowledge acquisition,Humanoid robots | Robot learning,Computer vision,Interactive Learning,Computer science,Object model,Learning object,Artificial intelligence,Error-driven learning,Visual perception,Knowledge acquisition,Humanoid robot | Journal |
Volume | Issue | ISSN |
56 | 11 | Robotics and Autonomous Systems |
Citations | PageRank | References |
13 | 0.95 | 20 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hartwig Holzapfel | 1 | 164 | 12.24 |
| Daniel Neubig | 2 | 13 | 1.28 |
| Alex Waibel | 3 | 6343 | 1980.68 |