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Extrinsic Parameter Calibration Method for a Visual/Inertial Integrated System with a Predefined Mechanical

Chenguang Ouyang1, Shuai Shi2,3, Zheng You4

  • 1State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing 100084, China.

Sensors (Basel, Switzerland)
|July 25, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces a new method for calibrating visual/inertial systems using geometric constraints and manual swinging. This approach accurately determines extrinsic parameters for cameras and inertial measurement units (IMUs), enhancing navigation precision.

Keywords:
corner detectionextrinsic parameter calibrationmotion blurvisual/inertial integrated system

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Area of Science:

  • Robotics
  • Computer Vision
  • Sensor Fusion

Background:

  • Accurate extrinsic parameter calibration is vital for visual/inertial integrated systems.
  • Existing methods may have limitations in precision or complexity.

Purpose of the Study:

  • To develop a novel, accurate, and efficient method for calibrating extrinsic parameters of cameras and IMUs in integrated systems.
  • To leverage geometric constraints and sensor complementarity for improved calibration.

Main Methods:

  • A manual swing-based calibration technique utilizing object-space geometric constraints.
  • Alignment of camera and IMU frames to a predefined system body frame.
  • Exploiting checkerboard patterns for camera calibration and angular velocity/acceleration for IMU calibration.

Main Results:

  • Achieved high accuracy in extrinsic parameter calibration: 0.04° for Euler angles and 0.15 mm for position components (1σ).
  • Demonstrated the complementary benefits of camera and IMU data, with IMU aiding visual detection and camera data mitigating IMU drift.

Conclusions:

  • The proposed method offers a robust solution for extrinsic parameter calibration in visual/inertial systems.
  • The technique enhances navigation and measurement accuracy through precise sensor alignment.