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Stereovision-Based Ego-Motion Estimation for Combine Harvesters.

Haiwen Chen1, Jin Chen1, Zhuohuai Guan2

  • 1Mechanical Engineering School, Jiangsu University, Zhenjiang 212013, China.

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|September 9, 2022
PubMed
Summary

This study introduces a new stereo vision method for autonomous combine harvesters to estimate Six Degree of Freedom (DoF) ego-motion. The system achieves accurate, real-time pose estimation crucial for navigation and harvesting operations.

Keywords:
FREAK featurecombine harvestersego-motionstereo cameravisual odometry

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Area of Science:

  • Robotics
  • Computer Vision
  • Agricultural Engineering

Background:

  • Ego-motion estimation is vital for autonomous combine harvester navigation and harvesting.
  • Accurate real-time pose estimation is required for high-level autonomous functions.

Purpose of the Study:

  • To develop a novel stereo vision-based approach for estimating the Six Degree of Freedom (DoF) ego-motion of combine harvesters.
  • To achieve real-time performance and high accuracy for online ego-motion estimation.

Main Methods:

  • Tracking 3D landmarks triangulated from stereo-matched features.
  • Minimizing reprojection error for Six Degree of Freedom (DoF) ego-motion estimation.
  • Employing local bundle adjustment within a sliding window for joint refinement of structure and motion.
  • Utilizing a two-threaded architecture for real-time processing.

Main Results:

  • The proposed method successfully estimates ego-motion from stereo image sequences.
  • Quantitative tests on real agricultural data demonstrated favorable accuracy.
  • The system achieved real-time performance, outputting pose information at 10 Hz.

Conclusions:

  • The developed stereo vision system provides accurate and real-time ego-motion estimation for autonomous combine harvesters.
  • The approach is suitable for supporting navigation and harvesting functions in agricultural settings.
  • The use of a stereo camera facilitates true-scale estimation and simplifies system startup.