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Robot Localisation Using UHF-RFID Tags: A Kalman Smoother Approach †.

Farhad Shamsfakhr1, Andrea Motroni2, Luigi Palopoli3

  • 1Department of Industrial Engineering, University of Trento, 38123 Trento, Italy.

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|January 26, 2021
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Summary
This summary is machine-generated.

This study introduces an Extended Kalman Smoother for precise indoor vehicle localization and trajectory reconstruction using UHF-RFID technology. The method achieves accurate results in simulations and real-world experiments for autonomous systems.

Keywords:
Kalman smootherRadio Frequency IDentificationrobot localisation

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Area of Science:

  • Robotics
  • Localization and Mapping
  • Sensor Fusion

Background:

  • Autonomous vehicles are crucial for smart warehouses and factories, demanding efficient indoor localization.
  • Current localization methods face challenges in accuracy, affordability, and real-time application for mobile agents.

Purpose of the Study:

  • To design an Extended Kalman Smoother for simultaneous localization and trajectory reconstruction of indoor mobile agents.
  • To evaluate the performance of the proposed method using UHF-RFID passive technology through simulations and experimental analysis.

Main Methods:

  • Sensor-fusion approach combining UHF-RFID passive technology with an Extended Kalman Smoother.
  • Extensive simulations to determine optimal smoother window length and assess the impact of missing measurements.
  • Monte Carlo simulations to evaluate accuracy across various vehicle trajectories and velocities.
  • Experimental validation using a unicycle wheeled robot in an indoor environment.

Main Results:

  • The Extended Kalman Smoother effectively localizes mobile agents and reconstructs their trajectories.
  • Simulations demonstrated the method's robustness to missing measurements and varying operational parameters.
  • Experimental analysis yielded position and orientation root mean square errors of 15 cm and 0.2 rad, respectively.

Conclusions:

  • The proposed Extended Kalman Smoother provides an effective and accurate solution for indoor vehicle localization and trajectory reconstruction.
  • UHF-RFID passive technology integrated with sensor fusion offers a promising approach for real-time applications in autonomous systems.
  • The method's performance in real-world scenarios validates its potential for smart warehouse and factory environments.