A waypoint tracking controller for autonomous road vehicles using ROS framework

Automated Driving Systems (ADSs) require robust and scalable control systems in order to achieve a safe, efficient and comfortable driving experience. Most global planners for autonomous vehicles provide as output a sequence of waypoints to be followed. This paper proposes a modular and scalable way...

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Detalles Bibliográficos
Autores: Gutiérrez Moreno, Rodrigo, López Guillén, María Elena, Pérez Gil, Óscar, Barea Navarro, Rafael|||0000-0002-4179-6100, Bergasa Pascual, Luis Miguel|||0000-0002-0087-3077, Gómez Huélamo, Carlos, Egido Sierra, Javier del, López Fernández, Joaquín
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universidad de Alcalá (UAH)
Repositorio:e_Buah Biblioteca Digital Universidad de Alcalá
Idioma:inglés
OAI Identifier:oai:ebuah.uah.es:10017/45409
Acceso en línea:http://hdl.handle.net/10017/45409
https://dx.doi.org/10.3390/s20144062
Access Level:acceso abierto
Palabra clave:Path tracking control
Autonomous road vehicles
Robot Operating System (ROS)
Electrónica
Electronics
Descripción
Sumario:Automated Driving Systems (ADSs) require robust and scalable control systems in order to achieve a safe, efficient and comfortable driving experience. Most global planners for autonomous vehicles provide as output a sequence of waypoints to be followed. This paper proposes a modular and scalable waypoint tracking controller for Robot Operating System (ROS)-based autonomous guided vehicles. The proposed controller performs a smooth interpolation of the waypoints and uses optimal control techniques to ensure robust trajectory tracking even at high speeds in urban environments (up to 50 km/h). The delays in the localization system and actuators are compensated in the control loop to stabilize the system. Forward velocity is adapted to path characteristics using a velocity profiler. The controller has been implemented as an ROS package providing scalability and exportability to the system in order to be used with a wide variety of simulators and real vehicles. We show the results of this controller using the novel and hyper realistic CARLA Simulator and carrying out a comparison with other standard and state-of-art trajectory tracking controllers.