<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This study validates EKF-SLAM for indoor autonomous vehicles by experimentally integrating the MPU6050 sensor and encoder data using an extended Kalman filter. Real-world tests show significant improvements, achieving high accuracy with just 1% and 3% errors in the X and Y axes. RPLiDAR A1M8 is utilized for mapping, producing accurate maps visualized through RViz-ROS. The research demonstrates the novelty and practical utility of EKF-SLAM in real-world scenarios, showcasing unprecedented effectiveness and precision.</p>
</abstract>

This study validates EKF-SLAM for indoor autonomous vehicles by experimentally integrating the MPU6050 sensor and encoder data using an extended Kalman filter. Real-world tests show significant improvements, achieving high accuracy with just 1% and 3% errors in the X and Y axes. RPLiDAR A1M8 is utilized for mapping, producing accurate maps visualized through RViz-ROS. The research demonstrates the novelty and practical utility of EKF-SLAM in real-world scenarios, showcasing unprecedented effectiveness and precision.

Experimental Validation: Perception and Localization Systems for Autonomous Vehicles using the Extended Kalman Filter Algorithm

Beehive Intelligent Robotics Laboratory (BIRL)

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

This study validates EKF-SLAM for indoor autonomous vehicles by experimentally integrating the MPU6050 sensor and encoder data using an extended Kalman filter....

Experimental Validation: Perception and Localization Systems for Autonomous Vehicles using the Extended Kalman Filter Algorithm

Article Category: Article

Online veröffentlicht: 07. Feb. 2024

Seitenbereich: -

Eingereicht: 28. Aug. 2023

DOI: https://doi.org/10.2478/ijssis-2024-0002

Schlüsselwörter
Experimental validation, extended Kalman filter, ground mobile robot, robot operating system, simultaneous localization and mapping

© 2024 Bambang Lelono Widjiantoro et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Experimental Validation: Perception and Localization Systems for Autonomous Vehicles using the Extended Kalman Filter Algorithm

Article Category: Article

Online veröffentlicht: 07. Feb. 2024

Seitenbereich: -

Eingereicht: 28. Aug. 2023

DOI: https://doi.org/10.2478/ijssis-2024-0002

SchlüsselwörterExperimental validation, extended Kalman filter, ground mobile robot, robot operating system, simultaneous localization and mapping

© 2024 Bambang Lelono Widjiantoro et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Experimental validation, extended Kalman filter, ground mobile robot, robot operating system, simultaneous localization and mapping