Name
Abstract | ||
|---|---|---|
This paper provides an overview of the main developments of the Tech United Eindhoven RoboCup @Home team. Tech United uses an advanced world modeling system called the Environment Descriptor. It allows straightforward implementation of localization, navigation, exploration, object detection u0026 recognition, object manipulation and robot-robot cooperation skills based on the most recent state of the world. Other important features include object and people detection via deep learning methods, a GUI, speech recognition, natural language interpretation and a chat interface combined with a conversation engine. Recent developments that aided with obtaining the victory during RoboCup 2019 include pointing detection, usage of HSR’s display, a people detector and the addition of a custom keyboard in the chat interface. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/978-3-030-35699-6_43 | RoboCup |
Field | DocType | Citations |
Computer vision,Object detection,Conversation,Computer science,Human–computer interaction,Natural language,Victory,Artificial intelligence,Deep learning | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 14 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. F. B. van der Burgh | 1 | 0 | 0.34 |
| J. J. M. Lunenburg | 2 | 0 | 0.34 |
| R. P. W. Appeldoorn | 3 | 0 | 0.34 |
| L. L. A. M. van Beek | 4 | 0 | 0.34 |
| J. Geijsberts | 5 | 0 | 0.34 |
| L. G. L. Janssen | 6 | 0 | 0.34 |
| P. van Dooren | 7 | 0 | 0.34 |
| H. W. A. M. van Rooy | 8 | 0 | 0.34 |
| A. Aggarwal | 9 | 0 | 0.34 |
| S. Aleksandrov | 10 | 0 | 0.34 |
| K. Dang | 11 | 0 | 0.34 |
| Albert T. Hofkamp | 12 | 0 | 0.34 |
| D. van Dinther | 13 | 0 | 0.34 |
| René van de Molengraft | 14 | 194 | 23.48 |