DocumentCode
3743238
Title
Parameter estimation for the bivariate wrapped normal distribution
Author
Gerhard Kurz;Uwe D. Hanebeck
Author_Institution
Intelligent Sensor-Actuator-Systems Laboratory (ISAS), Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology (KIT), Germany
fYear
2015
Firstpage
1192
Lastpage
1198
Abstract
Correlated uncertain angular quantities can be modeled using the bivariate wrapped normal distribution. In this paper, we focus on the problem of estimating the distribution´s parameters from a given set of samples. For this purpose, we propose several new parameter estimation methods and compare them to estimation techniques found in literature. All methods are thoroughly evaluated in simulations. One of the novel methods is shown to combine the advantages of maximum likelihood estimation and moment-based methods, thus outperforming current state-of-the-art techniques.
Keywords
"Gaussian distribution","Correlation","Parameter estimation","Maximum likelihood estimation","Robots","Random variables","Manifolds"
Publisher
ieee
Conference_Titel
Decision and Control (CDC), 2015 IEEE 54th Annual Conference on
Type
conf
DOI
10.1109/CDC.2015.7402373
Filename
7402373
Link To Document