Name
Abstract | ||
|---|---|---|
The future of robotics predicts that robots will integrate themselves more every day with human beings and their environments. To achieve this integration, robots need to acquire information about the environment and its objects. There is a big need for algorithms to provide robots with these sort of skills, from the location where objects are needed to accomplish a task up to where these objects are considered as information about the environment. This paper presents a way to provide mobile robots with the ability-skill to detect objets for semantic navigation. This paper aims to use current trends in robotics and at the same time, that can be exported to other platforms. Two methods to detect objects are proposed, contour detection and a descriptor based technique, and both of them are combined to overcome their respective limitations. Finally, the code is tested on a real robot, to prove its accuracy and efficiency. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.3390/s140406734 | SENSORS |
Keywords | Field | DocType |
mobile robots,semantic navigation,object detection,contour detection,descriptor detection,image correlation | Computer vision,Object detection,Semantic navigation,Computer science,Future of robotics,sort,Artificial intelligence,Robot,Mobile robot,Semantics,Robotics | Journal |
Volume | Issue | ISSN |
14 | 4 | 1424-8220 |
Citations | PageRank | References |
10 | 0.74 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carlos Astua | 1 | 10 | 0.74 |
| Ramon Barber | 2 | 10 | 3.78 |
| Jonathan Crespo | 3 | 19 | 4.10 |
| Alberto Jardon | 4 | 10 | 0.74 |