Design of Automatic Recycling Robot Based on YOLO Target Detection

被引：2
|
作者：
Li, Chuan [1 ]
Shu, Manming [1 ]
Du, Ling [1 ]
Tan, Haoyue [1 ]
Wei, Lang [1 ]
机构：
[1] Southwest Petr Univ, Sch Infounat, Nanchong, Peoples R China
来源：
2022 ASIA CONFERENCE ON ALGORITHMS, COMPUTING AND MACHINE LEARNING (CACML 2022) | 2022年
关键词：
YOLO target detection; mechanical control; item recovery; PWM control;
D O I：
10.1109/CACML55074.2022.00059
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In order to achieve automatic item grasping and recovery, we propose a system design method based on YOLO v4 automatic recovery robot, using the higher computing power of Jetson Nano and STM32F103ZET6 computing units, processing image information to control the operation of the robot system, with six degrees of freedom PWM robot arm to accurately grasp the items. After system testing, the average item recognition rate exceeds 98.5%, and the recovery success rate exceeds 96%, truly achieving automatic search, grasp, recovery, and return end-to-end operation.
引用
收藏
页码：310 / 315
页数：6
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