一种用于实时控制物流仓库寻迹机器人的编码和解码方法

 李海博1,王德麾2*,樊庆文1,2,裴宏亮1,赵志键1,李焕1

(1.四川大学 制造科学与工程学院,四川 成都 610065;2.四川大学 空天科学与工程学院,四川 成都 610065)
摘要:根据机器人视觉原理,设计了一种基于简单图元的非同步流编码。流编码由“F”、“T”、“R”三种图元组成,分别表示“0”、“1”、“复码”,设计了编码和解码规则,通过图像识别可以将流编码(图形)编译为计算机原始码。较传统的条形码和二维码,流编码具有编码和解码简单、信息量大、识别准确率高、能够在寻迹机器人运动过程中完成解码的特点,满足物流仓库对寻迹机器人的控制和定位的要求,提高物流仓库运行效率。该编码和解码方法可以广泛应用于信息识别和传输领域,取代条形码和二维码。
关键词:流编码;寻迹机器人;机器视觉;编码;解码
中图分类号:TP242 文献标志码:A doi:10.3969/j.issn.1006-0316.2019.01.014
文章编号:1006-0316 (2019) 01-0064-04
A Coding and Decoding Method for Real-Time Control of Tracking Robot in Logistics Warehouse
LI Haibo1,WANG Dehui2,FAN Qingwen1,2,PEI Hongliang1,ZHAO Zhijian1,LI Huan1
( 1.School of Manufacturing Science & Engineering, Sichuan University, Chengdu 610065, China; 2.School of Aeronautics Science & Engineering, Sichuan University, Chengdu 610065, China )
Abstract:According to the principle of robot vision, An asynchronous flowing code based on simple patterns is designed. The flowing code is composed of three elements: "F", "T" and "R", which denotes "0", "1" and "repetitive code" respectively. This paper designed rules of coding and decoding that flowing code (pattern) compiled into computer source code by image recognition. Compared with the traditional bar code and the two-dimensional code, flowing code has the characteristics of simple rules of encoding and decoding, carrying large amount of information, high recognition accuracy, and the ability to decode during the movement of the tracing robot ,which satisfies requirement of logistics warehouse to control and to locate the tracking robot and improves the operation efficiency of logistics warehouse.The theoretical methods of encoding and decoding presented by this article can be widely applied in the field of information identification and transmission, which can replace bar code and QR code.
Key words:flowing code;tracking robot;machine vision;coding;decoding
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收稿日期:2018-03-30
基金项目:汽车噪声振动和安全技术国家重点实验室开发基金(NVHSKL-201407)
作者简介:李海博(1994-),男,四川渠县人,硕士研究生,主要研究方向为机器视觉;樊庆文(1966-),男,山东济宁人,研究员,硕士研究生导师,主要方向为人机工程、机电工程。*通讯作者:王德麾(1982-),男,河南商丘人,博士,讲师,主要研究方向为机器视觉。
 

 

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