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Fast automatic docking control for electric tractors.

Pengpeng Li1, Yu Bai2, Weihua Li2,3,4

  • 1School of Astronautics, Harbin Institute of Technology, Harbin 150001, China.

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|April 13, 2026
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Summary
This summary is machine-generated.

This study introduces an advanced automatic docking system for electric tractors and semi-trailers, enhancing precision and safety in complex scenarios. The method uses sensor fusion and multi-strategy control for reliable, millimeter-level accuracy.

Keywords:
Automatic dockingAutonomous drivingElectric tractorFusion positioningPiecewise proportional-integral-differential

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Area of Science:

  • Robotics and Automation
  • Autonomous Vehicle Systems
  • Sensor Fusion Technology

Background:

  • Automated docking of heavy vehicles like electric tractors and semi-trailers presents significant challenges, particularly in narrow and long-distance scenarios.
  • Existing systems often struggle with sensor inaccuracies, environmental interferences, and precise control for successful docking maneuvers.

Purpose of the Study:

  • To develop and validate a robust automatic docking method for electric tractor-semi-trailer combinations.
  • To address heading-angle errors and distance-based detection inaccuracies in camera systems.
  • To achieve high-precision pose perception and a reliable docking success rate.

Main Methods:

  • Implemented a multi-sensor fusion high-precision positioning algorithm combining camera data with Light Detection and Ranging (Lidar).
  • Introduced angle deviation compensation for camera heading-angle errors and a piecewise coordinate compensation function for longitudinal distance.
  • Utilized a novel Lidar search-and-location method with combined small and large neighborhoods to mitigate point cloud interference.
  • Employed a multi-strategy docking control algorithm, including lateral deviation-based angle control, PID control, security checks, and risk avoidance.

Main Results:

  • Achieved millimeter-level pose-perception accuracy through Lidar repositioning.
  • Successfully compensated for camera errors related to mechanical issues and longitudinal distance.
  • Demonstrated reliable docking through a comprehensive multi-strategy control approach.
  • Verified the system's reliability and stability through extensive real-vehicle experiments.

Conclusions:

  • The proposed automatic docking method effectively integrates multi-sensor fusion and multi-strategy control for precise and stable electric tractor-semi-trailer docking.
  • The compensation techniques and Lidar-based repositioning significantly enhance accuracy and overcome common sensor limitations.
  • The system proves reliable and stable for practical applications in challenging docking environments.