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Academic Journal of Computing & Information Science, 2020, 3(4); doi: 10.25236/AJCIS.2020.030402.

Design of Wheeled Robot Based on Visual Navigation


He Yali, Zhang Songfeng, Li Xueliang, Wu Kuang, Guo Yanhua

Corresponding Author:
He Yali

Zhoukou Normal University, Zhoukou, Henan, China, 466001


With the rapid development and innovation of science technology, the traffic intelligence level is improved day by day. In order to enable the wheeled robot to drive autonomously, STM32F103RCT6 MCU was selected as the controller of the path recognition wheeled robot, OV7670 digital CMOS image sensor was selected as the path information acquisition sensor, and SCA60C inclination sensor is selected as the road slope information acquisition sensor, A wheeled robot based on visual navigation was designed. In addition, in this paper, we compiled the control program of the wheeled robot for path recognition through Keil μVision5 IDE development software, and realized the automatic path recognition and autonomous operation of the robot with hardware circuit, and improved the mechanical structure and control algorithm of the robot in debugging. It was proved that the robot designed in this paper has the advantages of reasonable structure, CMOS image sensor foresight, and image binarization is stable with visual navigation algorithm, which has obvious advantages compared with traditional path recognition robot.


Visual navigation; Path recognition; CMOS

Cite This Paper

He Yali, Zhang Songfeng, Li Xueliang, Wu Kuang, Guo Yanhua. Design of Wheeled Robot Based on Visual Navigation. Academic Journal of Computing & Information Science (2020), Vol. 3, Issue 4: 11-20. https://doi.org/10.25236/AJCIS.2020.030402.


[1] Meng Wusheng, Song Xiaoyu, Ma Wenjia. Research on path recognition of tracking smart car based on CMOS sensor[J]. Mechatronics, 2011(8): 25-29.
[2] Yu Fenghua, Lei Yuqiao, Hu Yujie, et al. Research on smart car algorithm based on OV7620 tracking[J]. Microcomputers and Applications, 2013, 32(17): 69-71.
[3] Bui T L, Doan P T, Kim H K, et al. Adaptive Motion Controller Design for an Omnidirectional AGV Based on Laser Sensor[J]. Lecture Notes in Electrical Engineering, 2014, 282: 509-523.
[4] Liu Cun, Ma Xuefeng. Precision positioning vision system for automated three-dimensional warehouse handling robots[J]. Robot, 1992(5): 53-56.
[5] Man Z G, Ye W H, Zhao P, et al. Research on RFID and Vision-Based AGV Navigation[J]. Advanced Materials Research, 2010, 136: 298-302.
[6] Su Hui, Liu Lujing. Research and Application of Navigation Technology of Intelligent Inspection Robot in Power Plant[J]. Electronic Testing, 2016(23): 40-41.
[7] Wang Jilin. Research on visual navigation technology of intelligent tracked vehicles [D]. Changchun: Jilin University, 2004.
[8] Li Xinde, Wu Xuejian, Zhu Bo, et al. A dynamic environment visual navigation method based on hand-drawn maps [J]. Robot, 2011, 33(4): 490-501.
[9] Chen Hao. Research on path recognition technology in smart car visual navigation [D]. Wuhan: Wuhan University of Technology, 2010.
[10] Wang Rongben, Chu Jiangwei, Feng Yan, etc. A practical AGV design for visual navigation[J]. Chinese Journal of Mechanical Engineering, 2002(11): 135-138.
[11] Wang Hui. Research on the path recognition and control strategy of smart cars [D]. Changchun: Jilin University, 2009.