Name
Abstract | ||
|---|---|---|
We present Open-EASE, a cloud-based knowledge base of robot experience data that can serve as episodic memory, providing a robot with comprehensive information for autonomously learning manipulation tasks. Open-EASE combines both robot and human activity data in a common, semantically annotated knowledge base, including robot poses, object information, environment models, the robot’s intentions and beliefs, as well as information about the actions that have been performed. A powerful query language and inference tools support reasoning about the data and retrieving information based on semantic queries. In this paper, we focus on applications of Open-EASE in the context of autonomous learning. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/s13218-015-0364-1 | KI |
Keywords | Field | DocType |
Episodic Memory, Pane, Query Language, Image Pane, Robotic Agent | Robot learning,Episodic memory,Query language,Inference,Computer science,Artificial intelligence,Knowledge base,Robot,Autonomous learning,Machine learning,Cloud computing | Journal |
Volume | Issue | ISSN |
29 | 4 | 1610-1987 |
Citations | PageRank | References |
2 | 0.38 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Moritz Tenorth | 1 | 615 | 32.70 |
| Jan Oliver Winkler | 2 | 2 | 2.07 |
| Daniel Beßler | 3 | 3 | 3.12 |
| Michael Beetz | 4 | 3784 | 284.03 |