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Calibration of Mobile Robots Using ATOM.

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Summary
This summary is machine-generated.

This study introduces a new calibration method for mobile manipulators, improving accuracy even with imprecise localization systems. The Atomic Transformations Optimization Method (ATOM) enhances sensor and motion coordinate system calibration for diverse robotic systems.

Keywords:
ROSextrinsic calibrationintrinsic calibrationmulti-modalmulti-sensorregistration

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Area of Science:

  • Robotics
  • Sensor Fusion
  • Calibration Techniques

Background:

  • Accurate calibration is crucial for mobile manipulators, involving sensor-to-motion and localization transformations.
  • Existing methods lack flexibility for systems with multiple sensor types.

Purpose of the Study:

  • To develop a flexible calibration approach for multi-sensor, multi-modal mobile manipulators.
  • To simultaneously estimate sensor poses and calibration pattern positions, even with imprecise localization.

Main Methods:

  • Integration of a novel calibration approach into the Atomic Transformations Optimization Method (ATOM).
  • Formulation of calibration as an extended optimization problem to estimate multiple transformations concurrently.
  • Validation using simulations and real-world case studies.

Main Results:

  • Demonstrated improved calibration accuracy for mobile manipulators.
  • Showcased effectiveness across diverse sensor modalities.
  • Validated the robustness of the ATOM framework.

Conclusions:

  • The proposed ATOM-integrated calibration method offers enhanced precision and flexibility.
  • This approach is effective for complex mobile robotic systems with varied sensors.
  • It addresses limitations in current mobile manipulator calibration techniques.