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Mobile Robot Localization via Unscented Kalman Filter

Lasmadi Lasmadi, Freddy Kurniawan, Denny Dermawan, Gilang Nugraha Putu Pratama

Year
2019
Citations
10

Abstract

Mobile robot localization concerns estimating the position and heading of the robot relative to its environment. Basically, the mobile robot moves around without initial knowledge of the environment. Therefore, a scheme to handle it is necessary, such as the Kalman Filters. Rather than the Extended Kalman Filter, we choose to employ the sigma points approach. In this paper, we take into consideration the method proposed by Van Der Merwe to determine the sigma points in Unscented Kalman Filter. The simulation and results verify that the Unscented Kalman Filter works pretty well for locating the mobile robot.

Keywords

Kalman filterExtended Kalman filterHeading (navigation)Mobile robotFast Kalman filterComputer scienceUnscented transformRobotSimultaneous localization and mappingControl theory (sociology)

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