首页 | 本学科首页   官方微博 | 高级检索  
     

基于图像识别的水下机器人自主避障系统
引用本文:秦峰,刘甜甜,尤海鹏,麦宇庭,赵黎明,陈言俊. 基于图像识别的水下机器人自主避障系统[J]. 兵工自动化, 2012, 31(11): 87-90
作者姓名:秦峰  刘甜甜  尤海鹏  麦宇庭  赵黎明  陈言俊
作者单位:1. 山东大学工程训练中心,济南 250002
2. 山东大学控制科学与工程学院,济南 250061
3. 山东大学软件学院,济南 250101
摘    要:随着人类海洋活动的发展,水下自主机器人成为海洋勘察和科学研究的重要装备。设计一种基于图像识别的水下机器人自主避障系统,在无人干预的条件下实现机器人水下自主巡航、规避障碍、上浮下潜和实时数据传输。该系统采用CMOS模拟摄像头结合LM1881视频分离芯片提取视频模拟信号,MC9S12XS128单片机外部中断功能和内部AD转换器转换成数字信号,被转换出来的数据直接使用边缘检测算法实现障碍物的识别。数字信号和视频流也会经nRF24L01无线数据模块传到上位机,上位机将数据接收后进行相应显示,并可直接显示视频流,对水下环境进行实时监控。同时无线视频采集卡的影像模块采用OpenCV库进行的二次开发,完成上位机更加复杂的图像识别算法。并通过实例进行实验验证。实验结果表明,该系统能通过图像识别实现自主的水底探测和避障,具有较高的性价比和实用价值。

关 键 词:图像识别  水下机器人  边缘检测算法  OpenCV
收稿时间:2013-03-19

Autonomous Avoidance System of Underwater Robot Based on Image Recognition
Qin Feng,Liu Tiantian,You Haipeng,Mai Yuting,Zhao Liming,Chen Yanjun. Autonomous Avoidance System of Underwater Robot Based on Image Recognition[J]. Ordnance Industry Automation, 2012, 31(11): 87-90
Authors:Qin Feng  Liu Tiantian  You Haipeng  Mai Yuting  Zhao Liming  Chen Yanjun
Affiliation:1. Engineering Training Center, Shandong University, Jinan 250002, China; 2. School of Control Science & Engineering, Shandong University, Jinan 250061, China; 3. College of Software, Shandong University, Jinan 250101, China)
Abstract:With the development of human activities in the oceans, underwater autonomous robots have become important equipments for marine surveying and scientific research. In this paper, an avoidance system of autonomous underwater vehicle (AUV) is designed based on the image recognition technology, implementing underwater autonomous cruise, avoiding obstacles, floating and diving, real-time data transmission. The system uses a CMOS analog camera and LMI881 video separation chip to extract the analog video signal. The analog video signal is converted to digital signal by the MC9S 12XS 128 single chip external interruption function and internal AD transducer. Then the edge detection algorithm is used to recognize obstacles through the digital video signal. The digital signal and video streaming will be transmitted to the upper computer by nRF24L01 wireless data module. After the data is received, the program running on the host computer will display the data and picture to the screen, in order to monitor the underwater situation in real-time. At the same time, the video module of wireless video collection card uses OpenCV base to secondary development and realize more complex algorithm of upper PC. The results show that system realizes functions of obstacle avoidance and underwater surveying, thus indicating higher cost performance and practical significance.
Keywords:image recognition  underwater robot  edge detection algorithm  OpenCV
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《兵工自动化》浏览原始摘要信息
点击此处可从《兵工自动化》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号