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

Bambang Lelono Widjiantoro*, Katherin Indriawati, T. S.N. Alexander Buyung, Kadek Dwi Wahyuadnyana

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
JournalInternational Journal on Smart Sensing and Intelligent Systems
Volume17
Issue number1
DOIs
Publication statusPublished - 1 Jan 2024

Keywords

  • Experimental validation
  • extended Kalman filter
  • ground mobile robot
  • mapping
  • robot operating system
  • simultaneous localization

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