Investigation on Intermittent Observation in Mobile Robot Localization with Fuzzy Logic Technique
This paper deals with an analysis of intermittent observations for mobile robot localization with Fuzzy Logic approach. Mobile robot can easily lost its sight during environment observations due to several factors such as sensor faulty, and dynamic conditions. This can lead to erroneous estimation a...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | en en |
| Published: |
IEEE
2017
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/15311/1/fkee-2016-hamzah-Investigation%20on%20Intermittent%20Observation1.pdf http://umpir.ump.edu.my/id/eprint/15311/7/fkee-2017-hamzah-%20Investigation%20on%20Intermittent%20Observation%20in%20Mobile%20Robot.pdf http://umpir.ump.edu.my/id/eprint/15311/ https://doi.org/10.1109/I2CACIS.2016.7885282 |
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| Summary: | This paper deals with an analysis of intermittent observations for mobile robot localization with Fuzzy Logic approach. Mobile robot can easily lost its sight during environment observations due to several factors such as sensor faulty, and dynamic conditions. This can lead to erroneous estimation and the mobile robot become uncertain about its position. As a solution to this issue, this paper proposed a study on Fuzzy Logic technique to overcome such problem considering the Extended Kalman Filter(EKF) measurement innovation characteristic. The rules and fuzzy sets are designed such that it preserved good estimation whenever the relative angle and its relative distance measurements suddenly becomes larger than the previous measurements. The simulation results discusses two different cases observing the performance of the proposed technique. The results show that EKF with Fuzzy Logic technique is able to deal with intermittent observations if the design takes proper analysis and consideration on the measurement innovations. |
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