Name
Title | ||
|---|---|---|
A decoupled approach for simultaneous stochastic mapping and mobile robot localization. |
Abstract | ||
|---|---|---|
This paper introduces a decoupled approach of concurrent mapping and localization for mobile robots. Its theoretical aspects rely on recent techniques for correct uncertainty handling using stochastic models: covariance intersection and unscented transform. Further, stochastic constraints are considered as a way to minimize map incoherence with respect to the real environment. Experimental results obtained from multisensory data acquired in a large real environment illustrate the performance of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/IRDS.2002.1041449 | IROS |
Keywords | Field | DocType |
covariance analysis,mobile robots,path planning,transforms,uncertainty handling,covariance intersection,decoupled approach,map incoherence minimization,mobile robot localization,multisensory data,simultaneous stochastic mapping,uncertainty handling,unscented transform | Motion planning,Computer vision,Computer science,Covariance intersection,Control engineering,Unscented transform,Stochastic modelling,Artificial intelligence,Analysis of covariance,Uncertainty handling,Mobile robot | Conference |
Volume | Citations | PageRank |
1 | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Geovany Araujo Borges | 1 | 154 | 12.82 |
| Marie-José Aldon | 2 | 147 | 11.61 |