| Title |
Localization using Fuzzy-Extended Kalman Filter |
| Authors |
박성용(Park, Sung-Yong) ; 박종훈(Park, Jong-Hun) ; 왕해운(Wang, Hai-Yun) ; 노진홍(No, Jin-Hong) ; 허욱열(Huh, Uk-Youl) |
| DOI |
https://doi.org/10.5370/KIEE.2014.63.2.277 |
| Keywords |
Localization ; Mobile robots ; Fuzzy ; Extended Kalman filter |
| Abstract |
This paper proposes robot localization using Fuzzy-Extended Kalman Filter algorithm of the mobile robots equipped with least sensors. In order to improve the accuracy of the localization, we usually add the sensors or equipment. However, it increases the simulation time and expenses. This paper solves this problem using only the odometer and ultrasonic sensors to get the localization with the Fuzzy-Extended Kalman Filter algorithm method. By inputting the robot's angular velocity, sensor data variation, and residual errors into the fuzzy algorithm, we get the sensor weight factor to decide the sensor's importance. The performance of the designed method shows by the simulation and Pioneer 3-DX mobile robot test in the indoor environment. |