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Kinematics Calibration and Validation Approach Using Indoor Positioning System for an Omnidirectional Mobile Robot.

Alexandru-Tudor Popovici1, Constantin-Catalin Dosoftei2, Cristina Budaciu2

  • 1Department of Computer Engineering, "Gheorghe Asachi" Technical University of Iasi, 700050 Iasi, Romania.

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Summary
This summary is machine-generated.

This study introduces an improved calibration method for Omnidirectional Mobile Robots (OMR) to enhance indoor localization accuracy. The new approach significantly reduces motion errors, improving robot navigation in supply chains.

Keywords:
OMRaccurate localizationcalibrationindoor positioning systemvalidation

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Area of Science:

  • Robotics
  • Localization and Navigation
  • Supply Chain Management

Background:

  • Accurate localization of autonomous mobile robots (AMRs) is critical for efficient supply chain management.
  • Indoor localization presents unique challenges compared to GPS-based outdoor navigation.
  • Mechanical imperfections in robots can lead to significant motion errors, impacting operational accuracy.

Purpose of the Study:

  • To propose an extended calibration approach to improve Omnidirectional Mobile Robot (OMR) motion response.
  • To address challenges in indoor positioning accuracy for AMRs.
  • To reduce motion errors caused by mechanical build imperfections.

Main Methods:

  • Developed an extended calibration approach for OMRs.
  • Utilized an ultrasound-based positioning system with multilateration techniques.
  • Implemented a custom Robot Operating System (ROS) node in Matlab-Simulink for evaluation.

Main Results:

  • Reduced OMR motion error by up to seven times.
  • Achieved improved position estimation with a confidence coefficient.
  • Validated the enhanced calibration approach through generated reference trajectories.

Conclusions:

  • The proposed calibration method significantly enhances OMR motion response accuracy in indoor environments.
  • The approach effectively mitigates errors from mechanical imperfections and positioning system limitations.
  • This research contributes to more reliable autonomous robot navigation in logistics and supply chain applications.