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Trajectory tracking method based on the circulation of feasible path planning.

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This study introduces a novel trajectory tracking method for unmanned vehicles, enhancing self-decision and path following. The new approach effectively reduces tracking errors, ensuring vehicles accurately follow pre-set paths.

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Area of Science:

  • Robotics
  • Control Systems Engineering
  • Autonomous Navigation

Background:

  • Unmanned vehicles require sophisticated control methods for reliable operation.
  • Trajectory tracking is crucial for self-decision and path adherence in autonomous systems.
  • Existing methods may not fully account for vehicle dynamics and kinematics.

Purpose of the Study:

  • To propose a new trajectory tracking method for unmanned vehicles.
  • To enhance self-decision and trajectory tracking capabilities.
  • To address the limitations of current control strategies by incorporating vehicle dynamics and kinematics.

Main Methods:

  • Developed a trajectory tracking method based on feasible path planning circulation.
  • Implemented a multi-trace-points cooperative trajectory tracking control strategy.
  • Designed a lateral controller for precise trajectory tracking.
  • Created a simulation platform considering mechanical properties and characteristics.

Main Results:

  • The proposed method effectively reduces tracking errors.
  • Unmanned vehicles successfully followed pre-set virtual tracks.
  • The simulation platform validated the method's performance.
  • Feasible path generation is triggered upon exceeding tracking error thresholds.

Conclusions:

  • The novel trajectory tracking method enhances unmanned vehicle performance.
  • The approach ensures accurate path following by minimizing errors.
  • The method is robust and validated through simulation.
  • This contributes to more reliable autonomous navigation systems.