Research on improved dynamic window approach based on fuzzy logic for adaptive obstacle avoidance control in unmanned surface vehicles

Xinyuan Zhao; Qi Zhao; Jing Peng

doi:10.1117/12.3054438

3 January 2025 Research on improved dynamic window approach based on fuzzy logic for adaptive obstacle avoidance control in unmanned surface vehicles

Xinyuan Zhao, Qi Zhao, Jing Peng

Author Affiliations +

Proceedings Volume 13442, Fifth International Conference on Signal Processing and Computer Science (SPCS 2024); 134422E (2025) https://doi.org/10.1117/12.3054438
Event: Fifth International Conference on Signal Processing and Computer Science (SPCS 2024), 2024, Kaifeng, China

Abstract

An adaptive improved dynamic window approach based on fuzzy logic is proposed to address the challenges of avoiding dense obstacles and the poor applicability of the traditional dynamic window approach. First, a target point traction evaluation sub-function is added to the original evaluation function. Then, fuzzy logic is integrated into the improved dynamic window approach, allowing for real-time adjustment of the weight coefficients of various evaluation subfunctions based on environmental information. This enables local dynamic path planning for unmanned surface vehicles in various scenarios. Finally, the effectiveness of the algorithm is validated through simulation experiments.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xinyuan Zhao, Qi Zhao, and Jing Peng "Research on improved dynamic window approach based on fuzzy logic for adaptive obstacle avoidance control in unmanned surface vehicles", Proc. SPIE 13442, Fifth International Conference on Signal Processing and Computer Science (SPCS 2024), 134422E (3 January 2025); https://doi.org/10.1117/12.3054438

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