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Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

386
Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
386

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Updated: Jun 3, 2025

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A Robust Method for Validating Orientation Sensors Using a Robot Arm as a High-Precision Reference.

József Kuti1, Tamás Piricz1, Péter Galambos1

  • 1Antal Bejczy Center for Intelligent Robotics, Obuda University, 1034 Budapest, Hungary.

Sensors (Basel, Switzerland)
|January 8, 2025
PubMed
Summary

This study introduces a novel method to accurately validate orientation sensors using a robotic manipulator. The technique allows for precise sensor evaluation without exact alignment, improving robotic system reliability.

Keywords:
MEMSVR headsetgyroscopeinertial measurement unitorientation sensingrobotics

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Area of Science:

  • Robotics
  • Sensor Technology
  • Mechatronics

Background:

  • Orientation sensors are critical for robotic systems.
  • Accurate validation of these sensors is challenging.
  • Existing methods often require precise alignment and controlled conditions.

Purpose of the Study:

  • To present a robust and efficient method for validating orientation sensor accuracy.
  • To enable high-precision, automated, and comparative evaluation of sensors.
  • To facilitate efficient calibration and analysis of sensor errors.

Main Methods:

  • Utilizing a commercial robotic manipulator as a high-precision reference.
  • Determining rotational transformations between robot and sensor frames without precise alignment.
  • Generating repeatable excitation patterns under controlled conditions.

Main Results:

  • Demonstrated independence from exact rotation measurements between reference and sensor.
  • Enabled systematic and reproducible sensor testing.
  • Validated the effectiveness on an Inertial Navigation System module and SLAM-IMU fusion.

Conclusions:

  • The proposed method offers automated, high-precision validation of orientation sensors.
  • It addresses challenges in sensor calibration, drift, noise, and response delays.
  • The approach is versatile and reliable for various orientation sensing devices.