STM32-based image recognition intelligent logistics vehicle system

International Conference on Algorithms, Network, and Communication Technology (ICANCT) 2026

View at publisher
Authors: Huaizhong Zhu, Shiyuan Li, Zhongtang Li, Long Ding, Yunjiao Xu, Shan Zhu, Wei Liu, Hui Sun
DOI: 10.1117/12.3109579
Cited by: 0

Abstract

To address the demand for intelligent logistics handling, this project develops an STM32-based image recognition logistics vehicle system. With Taishan Series as the decision-making core and STM32F103 as the execution driver, it adopts a 70° high-definition camera for QR code decoding and a 120° wide-angle camera for environmental perception. The YOLOv11 model (8.1M parameters, accuracy >95%) is optimized via channel pruning and INT8 quantization, combined with HSV color segmentation (positioning error ±3mm) to solve complex lighting issues. Hardware supports precise X/Y/Z axis control (movement error

Fields of Study & Subjects

Advanced Neural Network Applications Smart Agriculture and AI Control and Dynamics of Mobile Robots

Publication details

Journal / source
International Conference on Algorithms, Network, and Communication Technology (ICANCT)
Pages
48–48
Publication date
17 February 2026
Language
EN