Effects of iteration in kalman filters family for improvement of estimation accuracy in simultaneous localization and mapping
- 1 January 2007
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- No. 21596247,p. 1-6
- https://doi.org/10.1109/aim.2007.4412453
Abstract
In this paper we investigate the role of iteration in kalman filters family for improvement of the estimation accuracy of states in Simultaneous Localization and Mapping (SLAM). The linearized error propagation existing in kalman filters family can result in large errors and inconsistency in the SLAM problem. One approach to alleviate this situation is the use of iteration in Extended Kalman Filter (EKF) and Sigma Point Kalman Filter (SPKF). We will describe that the iterated versions of kalman filters can increase the estimation accuracy and robustness of these filters against linear error propagation. Simulation results are presented to validate this improvement of state estimate convergence through repetitive linearization of the nonlinear model in EKFSLAM and SPKFSLAM algorithms.Keywords
This publication has 10 references indexed in Scilit:
- The Iterated Sigma Point Kalman Filter with Applications to Long Range StereoPublished by Robotics: Science and Systems Foundation ,2006
- Unscented Transformation of Vehicle States in SLAMPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Unscented SLAM for large-scale outdoor environmentsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Sigma-Point Kalman Filters for Nonlinear Estimation and Sensor-Fusion: Applications to Integrated NavigationPublished by American Institute of Aeronautics and Astronautics (AIAA) ,2004
- A counter example to the theory of simultaneous localization and map buildingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- The unscented Kalman filter for nonlinear estimationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Estimation with Applications to Tracking and NavigationPublished by Wiley ,2002
- A solution to the simultaneous localization and map building (SLAM) problemIEEE Transactions on Robotics and Automation, 2001
- Triangulation-based fusion of sonar data with application in robot pose trackingIEEE Transactions on Robotics and Automation, 2000
- Estimating Uncertain Spatial Relationships in RoboticsPublished by Springer Science and Business Media LLC ,1990