Title
Sonar and Video Data Fusion for Robot Localization and Environment Feature Estimation
Abstract
In this paper the localization and environment feature estimation problems are formulated in a stochastic setting, and an Extended Kalman Filtering (EKF) approach is proposed for the integration of odometric, video camera and sonar measures. The environment is supposed to be only partially known, and a probabilistic method for sensory data fusion aimed at increasing the environment knowledge is considered.
Year
DOI
Venue
2005
10.1109/CDC.2005.1583512
conference on decision and control
Keywords
DocType
ISSN
probabilistic method,stochastic processes,filtering,mobile robots,data fusion,simultaneous localization and mapping,uncertainty,extended kalman filter
Conference
0743-1546
ISBN
Citations 
PageRank 
0-7803-9567-0
2
0.40
References 
Authors
8
5
Name
Order
Citations
PageRank
A. Bonci1247.13
gianluca ippoliti220.40
a la manna320.40
S. Longhi4679.29
l sartini520.40