On the initialization of statistical optimum filters with application to motion estimation
The present paper is focusing on the initialization of statistical optimum filters for motion estimation in robotics. It shows that if certain conditions concerning the stability of a system are fulfilled, and some knowledge about the mean of the state is given, an initial error covariance matrix that is optimal with regard to the convergence behavior of the filter estimate might be analytically obtained. Easy algorithms for the n-dimensional continuous and discrete cases are presented. The...[Show more]
|Collections||ANU Research Publications|
|Source:||IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010) Proceedings|
|01_Kneip_On_the_initialization_of_2010.pdf||207.92 kB||Adobe PDF||Request a copy|
|02_Kneip_On_the_initialization_of_2010.pdf||372.54 kB||Adobe PDF||Request a copy|
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