吉林大学学报(信息科学版) ›› 2023, Vol. 41 ›› Issue (4): 759-766.

• • 上一篇    

 基于 Jetson Nano 的智能果蔬采摘机器人设计

张峻豪a , 吴 洵a , 吴 宁a , 曲瑞权a , 孟凡儒a , 张晨松b   

  1. 吉林大学 a. 通信工程学院; b. 电子科学与工程学院, 长春 130012
  • 收稿日期:2022-03-03 出版日期:2023-08-16 发布日期:2023-08-18
  • 通讯作者: 吴宁(1982— ), 女, 长春人, 吉林大学副教授, 硕士生导师, 主要从事非线性信号 分析传统算法及深度学习方法及其在图像识别、 地震勘探数据分析等领域的应用研究, ( Tel) 86-13596428654 ( E-mail) ning1337@ jlu. edu. cn。
  • 作者简介:张峻豪(2001— ), 男, 吉林通化人, 吉林大学本科生, 主要从事五自由度机械臂研究, ( Tel)86-18504355775(E-mail) 1095117641@ qq. com;
  • 基金资助:
    : 吉林大学优秀青年教师培养计划基金资助项目(NSFC42174153)

Design of Intelligent Fruit and Vegetable Harvesting Robot Based on Jetson Nano

ZHANG Junhao a , WU Xun a , WU Ning a , QU Ruiquan a , MENG Fanru a , ZHANG Chensong b   

  1. a. College of Communication Engineering; b. College of Electronic Science and Engineering, Jilin University, Changchun 130012, China
  • Received:2022-03-03 Online:2023-08-16 Published:2023-08-18

摘要:  针对目前人工果蔬采摘成本较高且国内果蔬采摘机器人发展较慢问题, 设计了一类智能果蔬采摘 机器人。 该机器人的设计采用 Jetson Nano 开发板进行效率更高的视觉识别( VI: Visual Identity) 运算和处 理方法, 视觉识别使用 YOLO V5s 算法, 运动控制应用五自由度机械臂的运动学正解进行分析并得出其 运动学正解公式, 进而得知机械臂活动空间, 末端执行器采用夹持爪子以便各类果蔬的采摘。 最终确定 了较为清晰的果蔬采摘智能结构, 结果表明, 采用 Jetson Nano 开发板使视觉识别算法运算速率提高 10 倍 以上, 通过对正解公式的分析使末端执行器运动更为精准, 在可接受偏差内较为完整的实现了果蔬采摘 功能。

关键词: 视觉识别, 深度学习, 机械臂, 运动控制

Abstract: Because of the high cost of artificial fruit and vegetable picking and slow development of domestic fruit and vegetable picking robots, an intelligent robot is designed to reduce labor costs and time costs. According to the College Students’ Innovative Entrepreneurial Training Program, the design process of the fruit and vegetable piking robot is studied, using NVIDIA Jetson Nano development board to improve VI( Visual Identity) computing efficiency. The VI algorithm adopts the YOLO V5s algorithm and the motion control part to analyze the forward kinematics solution of the 5-DOF( Degree-Of-Freedom) mechanical arm, the forward kinematics formula of the 5-DOF mechanical arm is derived, and thus finding out about its activity space. In the End-Effector section, the gripper is used to facilitate the picking of various fruits and vegetables. A clearer intelligent structure for fruit and vegetable picking is established, the speed of VI is increased by more than 10 times by using NVIDIA Jetson Nano. Through the analysis of the forward kinematics formula, the End-Effector Action is more accurate, and also the fruit and vegetable picking aiming is completely realized within an acceptable deviation.

Key words: visual identity, deep learning, mechanical arm, motion control

中图分类号: 

  • TP241