TY - GEN
T1 - A Preview Neuro-Fuzzy Controller Based on Deep Reinforcement Learning for Backing Up a Truck-Trailer Vehicle
AU - Bejar, Eduardo
AU - Moran, Antonio
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5
Y1 - 2019/5
N2 - Backing up truck-trailer vehicles is a required task in several industry sectors. Controllers that have been proposed to automate this process usually struggle when the vehicle is required to follow a nonlinear trajectory. This paper presents a neuro-fuzzy controller based on preview control and deep reinforcement learning for reverse parking truck-trailer vehicles. The controller consists of a deep neural network trained with reinforcement learning. A preview control signal is coupled into the trained controller to improve the control performance when tracking complex trajectories. Moreover, a fuzzy logic approach is used to avoid the jackknife state. Simulation results are presented to show that the controller is able to track circular and sinusoidal trajectories.
AB - Backing up truck-trailer vehicles is a required task in several industry sectors. Controllers that have been proposed to automate this process usually struggle when the vehicle is required to follow a nonlinear trajectory. This paper presents a neuro-fuzzy controller based on preview control and deep reinforcement learning for reverse parking truck-trailer vehicles. The controller consists of a deep neural network trained with reinforcement learning. A preview control signal is coupled into the trained controller to improve the control performance when tracking complex trajectories. Moreover, a fuzzy logic approach is used to avoid the jackknife state. Simulation results are presented to show that the controller is able to track circular and sinusoidal trajectories.
KW - artificial intelligence
KW - control systems
KW - deep learning
KW - reinforcement learning
KW - robotics
KW - self-driving vehicles
UR - http://www.scopus.com/inward/record.url?scp=85074087488&partnerID=8YFLogxK
U2 - 10.1109/CCECE.2019.8861534
DO - 10.1109/CCECE.2019.8861534
M3 - Conference contribution
AN - SCOPUS:85074087488
T3 - 2019 IEEE Canadian Conference of Electrical and Computer Engineering, CCECE 2019
BT - 2019 IEEE Canadian Conference of Electrical and Computer Engineering, CCECE 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Canadian Conference of Electrical and Computer Engineering, CCECE 2019
Y2 - 5 May 2019 through 8 May 2019
ER -