Based on BP neural network in obstacle avoidance in mobile robots

Jun Ji; Rui Hou; Zhi Lu; Xukun Zhang; Yinghuang Liu

doi:10.1117/12.3011586

7 December 2023 Based on BP neural network in obstacle avoidance in mobile robots

Jun Ji, Rui Hou, Zhi Lu, Xukun Zhang, Yinghuang Liu

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 129415J (2023) https://doi.org/10.1117/12.3011586
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

With the rapid development of robot technology, the application fields of robots are becoming increasingly widespread, as they can replace humans to complete some dangerous and complex tasks. The obstacle avoidance problem of mobile robots is one of the important research directions in robots and has great significance for study. This paper presents the obstacle avoidance problem of robots based on the BP neural network algorithm. The grid method of Matlab is used to establish an environmental map. The results show that this algorithm can accurately achieve obstacle avoidance for mobile robots.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jun Ji, Rui Hou, Zhi Lu, Xukun Zhang, and Yinghuang Liu "Based on BP neural network in obstacle avoidance in mobile robots", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 129415J (7 December 2023); https://doi.org/10.1117/12.3011586

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