A model-based reinforcement learning algorithm faced with the laser frequency sweep linearization for FMCW LiDAR

Haohao Zhao; Guohui Yuan; Zhuoran Wang

doi:10.1117/12.2652082

23 January 2023 A model-based reinforcement learning algorithm faced with the laser frequency sweep linearization for FMCW LiDAR

Haohao Zhao, Guohui Yuan, Zhuoran Wang

Author Affiliations +

Proceedings Volume 12557, AOPC 2022: Optical Sensing, Imaging, and Display Technology; 125572G (2023) https://doi.org/10.1117/12.2652082
Event: Applied Optics and Photonics China 2022 (AOPC2022), 2022, Beijing, China

Abstract

Artificial intelligence (AI) has been widely used in various fields of physics and engineering. In this work, we introduce the model-based reinforcement learning (MBRL), which is an important branch of machine learning, to the laser frequency sweep control for frequency modualted continous wave (FMCW) light detection and range (LiDAR). With the well designed neural network structure, the experimental results with control represent a significant improvement in the linearity of laser frequency sweep indicating that our proposed MBRL control method has the potential for complicated optical systems control.

Citation Download Citation

Haohao Zhao, Guohui Yuan, and Zhuoran Wang "A model-based reinforcement learning algorithm faced with the laser frequency sweep linearization for FMCW LiDAR", Proc. SPIE 12557, AOPC 2022: Optical Sensing, Imaging, and Display Technology, 125572G (23 January 2023); https://doi.org/10.1117/12.2652082

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available