Name
Abstract | ||
|---|---|---|
One of the long-term goals of our society is to build robots able to live side by side with humans. In order to do so, robots need to be able to reason in a qualitative way. To this end, over the last years, the Artificial Intelligence research community has developed a considerable amount of qualitative reasoners. The majority of such approaches, however, has been developed under the assumption that suitable representations of the world were available. In this paper, we propose a method for performing qualitative spatial reasoning in robotics on abstract representations of environments, automatically extracted from metric maps. Both the representation and the reasoner are used to perform the grounding of commands vocally given by the user. The approach has been verified on a real robot interacting with several non-expert users. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-24309-2_34 | AI*IA 2015: ADVANCES IN ARTIFICIAL INTELLIGENCE |
Field | DocType | Volume |
Spatial relation,Spatial intelligence,Semantic reasoner,Computer science,Metric map,Artificial intelligence,Robot,Robotics,Topological graph | Conference | 9336 |
ISSN | Citations | PageRank |
0302-9743 | 2 | 0.37 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guglielmo Gemignani | 1 | 41 | 5.73 |
| Roberto Capobianco | 2 | 40 | 9.78 |
| Daniele Nardi | 3 | 5968 | 545.67 |