| Autor: |
Ahmad, Hamzah, Muhammad, Badaruddin, Ramli, Mohd Syakirin, Noh, Maziyah Mat, Zain, Zainah Md |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2023, Vol. 2795 Issue 1, p1-8, 8p |
| Abstrakt: |
This paper aims to analyze the Extended Kalman Filter estimation behavior in mobile robot navigation during intermittent measurement. The study mainly focuses on a case of mobile robot moving in an environment and has lost its information on measurement data intermittently. Two cases of different noises are examined which are environment with Gaussian and non-Gaussian noise. During the mobile robot observations, the measurement data for specific landmarks is assumed to be unavailable for a specific period. The measurement error, measurement innovation and state covariance characteristics are continuously observed when measurement data is missing for certain landmarks to understand how the state estimation behaves. Theoretical analysis and simulation results are presented to illustrate the EKF performances which are found to be consistent with the literatures. The presented results indicated that the EKF performance on its estimation can be preserved at bounded error for different environment noise conditions. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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