Reinforcement Learning from Simulation to Real World Autonomous Driving using Digital Twin-Reference-Cited by-同舟云学术

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Reinforcement Learning from Simulation to Real World Autonomous Driving using Digital Twin

Published:2023 Issue:2 Volume:56 Page:1510-1515
ISSN:2405-8963
Container-title:IFAC-PapersOnLine
language:en
Short-container-title:IFAC-PapersOnLine

Author:

Voogd Kevin L.,Allamaa Jean Pierre,Alonso-Mora Javier,Son Tong Duy

Publisher

Elsevier BV

Subject

General Medicine

Reference19 articles.

1. Sim2real for autonomous vehicle control using executable digital twin;Allamaa;IFAC-PapersOnLine,2022

2. Path following with deep reinforcement learning for autonomous cars;Alomari,2021

3. Learning dexterous in-hand manipulation;Andrychowicz;The International Journal of Robotics Research,2020

4. Al-phastar: an evolutionary computation perspective;Arulkumaran,2019

5. Soft actor-critic: Of-policy maximum entropy deep reinforcement learning with a stochastic actor;Haarnoja,2018

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Artificial intelligence can regulate light and climate systems to reduce energy use in plant factories and support sustainable food production;Nature Food;2024-09-09

2. A Multi-Teacher Policy Distillation Framework for Enhancing Zero-Shot Generalization of Autonomous Driving Policies;IEEE Transactions on Vehicular Technology;2024-07

3. Decision Making for Autonomous Driving Stack: Shortening the Gap from Simulation to Real-World Implementations;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

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