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Robust Localization Mechanism Based on Finite State Machine.
The proposed robust localization methods are divided into the iteration method and closed-form algorithm.
Therefore, a reliable and robust localization of the signal source has to be applied.
Designing a robust localization algorithm to resist the complex environment is a challenge in this field.
The adaptive robust localization algorithms in this paper can be represented as follows.
This paper describes an efficient and robust localization system for indoor mobile robots and AGVs.
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Expression of Rbf1N-RFP using tissue-specific GAL4 drivers shows robust nuclear localization in larval salivary gland cells in addition to cytoplasmic and plasma membrane localization (Figure 2B).
In an oskar protein null, however, only 16% of the oocytes show a robust posterior localization of Kin:β-GAL, whereas 72% show a weak posterior enrichment, and 12% show no localization to the posterior at all.
Simulation results confirm also that Directional BSS is very robust against localization errors.
In this article, we propose a novel robust indoor localization algorithm under the framework of Bayesian filter.
In this paper, we have proposed a processing chain addressing safety at level crossings composed of a foreground extraction based on CICA followed by a robust 3D localization.
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