An indoor mobile robot positioning system based on radio-frequency identification

An indoor mobile robot positioning system based on radio-frequency identification

Jiansheng Peng Jian MiaoQingjin Wei Zhenwu Wan Yiyong Huang Shijie Tang 

Colleges of Physics and Mechanical and Electronic Engineering Hechi University, Yizhou 546300, China

Department of Information Engineering, Huaxia College Wuhan University of Technology, Wuhan 430000, Chian

Colleges and Universities Key Laboratory of Intelligent Integrated Automation (Guilin University of Electronic Technology), Guilin 541000, China

Corresponding Author Email: 
sheng120410@163.com
Page: 
313-322
|
DOI: 
https://doi.org/10.3166/JESA.50.313-322
| |
Published: 
31 August 2017
| Citation

OPEN ACCESS

Abstract: 

Based on radio-frequency identification (RFID), this paper designs an upper and lower computer control system to solve the problems of existing indoor mobile robot positioning techniques. The Matlab graphical user interface was employed to build the software platform (i.e. upper computer) of the information database in the mobile robot positioning system, while the STM 32-based mobile robot control was adopted to design the hardware control system (i.e. lower computer). In addition, the data transmission between the computers and the robot was realized using the serial communication technology in Matlab Toolbox and CC2530 wireless communication, laying the basis for robot positioning. The proposed control system was proved effective in enhancing the robot’s responsiveness and controllability and solving the problems of the lower computer (e.g. low computability and insufficient storage). This research marks the trend of mobile robot positioning technology..

Keywords: 

MATLAB GUI, RFID, positioning, indoor mobile robots, control box

1. Introduction
2. MATLAB serial communication
3. MATLAB GUI introduction and application
4. Indoor mobile robot PC interface design
5. RFID technology
6. Building a wireless communications platform
7. Indoor mobile robot control system implementation
8. Conclusion
Acknowledgment

This work is supported by the National Natural Science Foundation of China (Grant No. 61640305). This research was financially supported by the project of Thousands outstanding young teachers’ training in higher education institutions of Guangxi, Guangxi Colleges and Universities Key Laboratory Breeding Base of System Control and Information Processing, Hechi University research project start-up funds (XJ2015KQ004), Supported by Colleges and Universities Key Laboratory of Intelligent Integrated Automation (GXZDSY2016-04), Hechi City Science and Technology Project (1694-3-2) , Research on multi robot cooperative system based on artificial fish swarm algorithm (2017CFC811).

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