Name
Abstract | ||
|---|---|---|
This paper addresses the problem of dealing with different kinds of dynamic obstacles influencing a place recognition task. We improve an existing approach using independent Marcov chain grid maps (iMac). Furthermore, we add a fuzzy classification to exploit the iMac estimation to refine the likelihood field estimation. We can show that the proposed method increases the performance of place recognition, while still being a compact, interpretable framework. |
Year | Venue | Keywords |
|---|---|---|
2014 | Lecture Notes in Computer Science | iMac,fuzzy classifier,cognitive robotics,place recognition |
Field | DocType | Volume |
Cognitive robotics,Fuzzy classification,Computer science,Fuzzy logic,Exploit,Artificial intelligence,Fuzzy classifier,Perception,Machine learning,Grid | Conference | 8836 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Frank Bahrmann | 1 | 2 | 2.07 |
| Sven Hellbach | 2 | 63 | 9.77 |
| Sabrina Keil | 3 | 0 | 0.34 |
| Hans-Joachim Böhme | 4 | 143 | 20.86 |