Name
Abstract | ||
|---|---|---|
Many practical application in the field of robotic and perception are using angular data. In this work we present a multi-sensor multi-temporal data fusion filter for angular data. Most of the time, statistic filters, are designed on linear domain. In this work we propose a recursive filter defined on the circular domain with a von Mises distribution. In our application we consider a set of measurement taking at different instants and provided by different sensors. The sequential implementation of the recursive fusion filter we propose is deduced from the a posteriori distribution of the state vector, containing the angular direction and velocity. Temporal measurements are coming from several sensors. The feasibility and the contribution of our method are shown on synthetic data. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ROBIO.2009.5420492 | Robotics and Biomimetics |
Keywords | Field | DocType |
different sensor,multi-sensor multi-temporal data fusion,angular direction,statistic filter,posteriori distribution,recursive fusion filter,angular data,linear domain,different instant,synthetic data,circular domain,noise measurement,von mises distribution,mathematical model,temporal data,sensor fusion,kalman filters,noise,trajectory,sensors | Noise measurement,Control theory,A priori and a posteriori,Synthetic data,Artificial intelligence,Recursive filter,State vector,Pattern recognition,von Mises distribution,Algorithm,Sensor fusion,Kalman filter,Mathematics | Conference |
ISBN | Citations | PageRank |
978-1-4244-4775-6 | 19 | 1.38 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Monir Azmani | 1 | 21 | 2.49 |
| Serge Reboul | 2 | 25 | 7.02 |
| Jean-Bernard Choquel | 3 | 44 | 5.67 |
| Mohammed Benjelloun | 4 | 163 | 24.87 |