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

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.