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A Waypoint Tracking Controller for Autonomous Road Vehicles Using ROS Framework.

Rodrigo Gutiérrez1, Elena López-Guillén1, Luis M Bergasa1

  • 1Electronics Department, University of Alcalá, Campus Universitario, 28805 Alcalá de Henares, Spain.

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PubMed
Summary
This summary is machine-generated.

This study introduces a modular waypoint tracking controller for autonomous vehicles, enhancing safety and comfort. The system ensures robust trajectory tracking at high speeds by compensating for system delays and adapting velocity to path characteristics.

Keywords:
Robot Operating System (ROS)autonomous road vehiclespath tracking control

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Area of Science:

  • Robotics
  • Control Systems Engineering
  • Autonomous Driving

Background:

  • Automated Driving Systems (ADSs) rely on precise control for safe and efficient operation.
  • Current global planners for autonomous vehicles output waypoints, necessitating effective tracking controllers.
  • Urban environments present challenges for trajectory tracking due to speed and potential delays.

Purpose of the Study:

  • To propose a modular and scalable waypoint tracking controller for Robot Operating System (ROS)-based autonomous guided vehicles.
  • To enhance trajectory tracking performance, even at high speeds (up to 50 km/h) in urban settings.
  • To develop a controller adaptable for various simulators and real-world vehicles.

Main Methods:

  • Smooth interpolation of waypoints.
  • Application of optimal control techniques for robust trajectory tracking.
  • Compensation for localization and actuator delays within the control loop.
  • Implementation of a velocity profiler to adapt forward speed to path characteristics.
  • Development as an ROS package for scalability and exportability.

Main Results:

  • The proposed controller demonstrates robust trajectory tracking performance.
  • Effective compensation for system delays leads to a stabilized control system.
  • Velocity profiling ensures appropriate speed adaptation to varying path conditions.
  • The ROS package facilitates integration with diverse simulators (e.g., CARLA) and real vehicles.

Conclusions:

  • The developed modular waypoint tracking controller offers a scalable and robust solution for autonomous vehicles.
  • The controller's ability to handle delays and adapt velocity enhances performance in complex urban environments.
  • The ROS-based implementation promotes widespread adoption and integration in autonomous driving research and development.