@inproceedings{42eb8fad98814e3a9fecdaad9a129c7a,
title = "Reverse parking a car-like mobile robot with deep reinforcement learning and preview control",
abstract = "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.",
keywords = "control systems, deep learning, reinforcement learning, robotics, self-driving vehicles",
author = "Eduardo Bejar and Antonio Moran",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 9th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2019 ; Conference date: 07-01-2019 Through 09-01-2019",
year = "2019",
month = mar,
day = "12",
doi = "10.1109/CCWC.2019.8666613",
language = "English",
series = "2019 IEEE 9th Annual Computing and Communication Workshop and Conference, CCWC 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "377--383",
editor = "Satyajit Chakrabarti and Saha, {Himadri Nath}",
booktitle = "2019 IEEE 9th Annual Computing and Communication Workshop and Conference, CCWC 2019",
}