Robust Filter Development to Pursue Robotic Localization and Mapping Problem
This paper deals with the development of a robust filter known as H Filter , as an approach to provide alternative solutions in robotic localization and mapping problem. In this problem, normally the environment conditions and noise characteristics are unknown which makes the Kalman Filter approach...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/3533/ http://umpir.ump.edu.my/id/eprint/3533/1/Robust_filter_development_to_pursue_robotic_localization_and_mapping_problem.pdf |
| Summary: | This paper deals with the development of a robust filter known as H Filter , as an approach to provide alternative solutions in robotic localization and mapping problem. In this problem, normally the environment conditions and noise characteristics are unknown which makes the Kalman Filter approach suffers. H Filter is proposed due its advantage in estimating conditions in non-Gaussian noise which Kalman Filter cannot offer. The analysis is shown by comparing the performance between H infinity Filter and Extended Kalman Filter for the above problem. Based on the simulation analysis and preliminary experiments, there is a high reliability in estimation of H Filter compared to Extended Kalman Filter regarding the robot location and landmark positions. Hence, H Filter can provide better solution especially in specific environment conditions with unknown noise characteristics. |
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