Vision-based sample-efficient reinforcement learning framework for autonomous driving

A framework combines vision and sample-efficient reinforcement-learning based on guided policy search for autonomous driving. A controller extracts environmental information from vision and is trained to drive using reinforcement learning.

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Bibliographic Details
Main Authors Chiang, Su-Hui, Liu, Ming-Chang
Format Patent
LanguageEnglish
Published 31.08.2021
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
CONTROLLING
COUNTING
HANDLING RECORD CARRIERS
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
REGULATING
SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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Summary:A framework combines vision and sample-efficient reinforcement-learning based on guided policy search for autonomous driving. A controller extracts environmental information from vision and is trained to drive using reinforcement learning.
Bibliography:Application Number: US201815943223