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RAMM: A Robotic, Autonomous Magnetic field Mapper.

Shinjer Li1, Samuel J Rubin1,2, Tyler Meldrum1

  • 1William & Mary, Department of Chemistry, 540 Landrum Drive, Williamsburg, VA 23188, USA.

Hardwarex
|October 2, 2025
PubMed
Summary

We developed RAMM, a Robotic, Autonomous Magnetic field Mapper, for precise 3D magnetic field mapping. This affordable, Python-controlled system uses a Hall sensor for accurate measurements in scientific and industrial applications.

Keywords:
Magnetic fieldOpen-sourceRobotSpatial mapping

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Area of Science:

  • Physics
  • Robotics
  • Instrumentation

Background:

  • Accurate spatial mapping of magnetic fields is essential for diverse scientific, industrial, and medical applications.
  • Existing methods may be costly or lack comprehensive 3D measurement capabilities.

Purpose of the Study:

  • To introduce RAMM (Robotic, Autonomous Magnetic field Mapper), a novel, low-cost system for precise 3D magnetic field mapping.
  • To provide a flexible and accessible tool for researchers and educators.

Main Methods:

  • Utilized a delta-style 3D robot equipped with a three-axis Hall sensor.
  • Implemented programmatic control via a Python interface for automated volumetric measurements.
  • Tested the system with various permanent magnet configurations.

Main Results:

  • Demonstrated accurate measurement of magnetic field components (x, y, z) across millitesla to single-digit Tesla ranges.
  • Generated detailed 3D magnetic field maps for different magnet setups.
  • Validated system performance by showing agreement with manufacturer-reported field gradients.

Conclusions:

  • RAMM offers an easy-to-build, affordable solution for accurate magnetic field mapping.
  • The system is well-suited for both research and educational purposes.
  • Facilitates volumetric magnetic field characterization with high precision.