Reverse parking a car-like mobile robot with deep reinforcement learning and preview control

Eduardo Bejar, Antonio Moran Cardenas

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

8 Citas (Scopus)

Resumen

This paper presents a control technique for reverse parking car-like vehicles based on deep reinforcement learning and preview control. The deep deterministic policy gradient (DDPG) algorithm is used for training a neurocontroller using a reward function defined in terms of the desired final state of the system. A preview control approach is employed to leverage knowledge of a known a priori reference input to generate a predictive control signal coupled into the neurocontroller output. Simulation results are presented to validate the proposed method. Moreover, these results show that incorporating a preview control signal improves the parking time.
Idioma originalEspañol
Título de la publicación alojada2019 IEEE 9th Annual Computing and Communication Workshop and Conference, CCWC 2019
Páginas377-383
Número de páginas7
EstadoPublicada - 12 mar. 2019
Publicado de forma externa

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