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Path Planning and Trajectory Tracking for Automatic Guided Vehicles.

Yongwei Tang1,2, Jun Zhou1, Huijuan Hao2

  • 1School of Mechanical Engineering, Key Laboratory of High Efficiency and Clean Mechanical Manufacture, Ministry of Education, Shandong University, Jinan 250061, Shandong, China.

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Summary
This summary is machine-generated.

This study presents an advanced controller for automated guided vehicles (AGVs), optimizing route planning and trajectory tracking for efficient manufacturing and logistics operations. The developed method ensures precise path following and minimal position error.

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Area of Science:

  • Robotics and Automation
  • Industrial Engineering
  • Control Systems

Background:

  • Automated guided vehicle (AGV) technology is crucial for modern manufacturing and logistics.
  • AGVs offer high intelligence and flexibility through features like autonomous route planning and task execution.
  • Existing research focuses on enhancing AGV capabilities for complex operational environments.

Purpose of the Study:

  • To investigate and develop effective route planning and tracking control for AGVs.
  • To design an advanced routing controller based on a kinematic model.
  • To validate the proposed methods through experimental simulation.

Main Methods:

  • Utilized a simple vehicle model for studying AGV dynamics.
  • Employed wireless communication for optimal route planning.
  • Developed a route-finding algorithm using geometric methods to model the working environment.
  • Designed an advanced routing controller based on the kinematic model.

Main Results:

  • The trajectory tracking controller demonstrated effectiveness, achieving near-zero position error after 2 seconds.
  • Path planning achieved a constant path length after more than 10 iterations, confirming method efficiency.
  • Simulations verified the controller's ability to accurately follow planned trajectories.

Conclusions:

  • The proposed route planning and tracking control system is effective for AGVs.
  • The developed geometric and kinematic approaches provide a robust solution for AGV navigation.
  • This research contributes to the advancement of intelligent automation in logistics and manufacturing.