JOURNAL ARTICLE

Mobile Robot Localization via Unscented Kalman Filter

Lasmadi LasmadiFreddy KurniawanDenny DermawanGilang Nugraha Putu Pratama

Year: 2019 Journal:   2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Vol: 40 Pages: 129-132

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 filter Extended Kalman filter Heading (navigation) Mobile robot Fast Kalman filter Computer science Unscented transform Robot Simultaneous localization and mapping Control theory (sociology) Alpha beta filter Position (finance) Artificial intelligence Computer vision Moving horizon estimation Engineering

Metrics

9
Cited By
0.95
FWCI (Field Weighted Citation Impact)
20
Refs
0.85
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering
Indoor and Outdoor Localization Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
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