On the initialization of statistical optimum filters with application to motion estimation
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Kneip, Laurent; Scaramuzza, D; Siegwart, Roland
Description
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]
dc.contributor.author | Kneip, Laurent | |
---|---|---|
dc.contributor.author | Scaramuzza, D | |
dc.contributor.author | Siegwart, Roland | |
dc.coverage.spatial | Taipei China | |
dc.date.accessioned | 2015-12-07T22:47:30Z | |
dc.date.created | October 18-22 2010 | |
dc.identifier.uri | http://hdl.handle.net/1885/26092 | |
dc.description.abstract | 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 applicability to non-linear systems is also pointed out. The convergence of a normal Kalman filter is analyzed in simulation using the discrete model of a theoretical example. | |
dc.publisher | IEEE Robotics and Automation Society | |
dc.relation.ispartofseries | IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010) | |
dc.source | IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010) Proceedings | |
dc.subject | Keywords: Convergence behaviors; Discrete models; Error covariance matrix; Optimum filters; Computer simulation; Covariance matrix; Estimation; Linear systems; Motion estimation; Intelligent robots | |
dc.title | On the initialization of statistical optimum filters with application to motion estimation | |
dc.type | Conference paper | |
local.description.notes | Imported from ARIES | |
local.description.refereed | Yes | |
dc.date.issued | 2010 | |
local.identifier.absfor | 090602 - Control Systems, Robotics and Automation | |
local.identifier.ariespublication | u4628727xPUB42 | |
local.type.status | Published Version | |
local.contributor.affiliation | Kneip, Laurent, College of Engineering and Computer Science, ANU | |
local.contributor.affiliation | Scaramuzza, D, Swiss Federal Institute of Technology Zurich (ETH Zurich) | |
local.contributor.affiliation | Siegwart, Roland, Swiss Federal Institute of Technology Zurich (ETH Zurich) | |
local.description.embargo | 2037-12-31 | |
local.bibliographicCitation.startpage | 1500 | |
local.bibliographicCitation.lastpage | 1506 | |
local.identifier.doi | 10.1109/IROS.2010.5652200 | |
local.identifier.absseo | 970109 - Expanding Knowledge in Engineering | |
dc.date.updated | 2016-02-24T11:15:00Z | |
local.identifier.scopusID | 2-s2.0-78651470833 | |
Collections | ANU Research Publications |
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