Multi-Vehicle Unmanned Following Operation Driving System Based on OpenMV

Yongcheng Ming, Rongbiao Yan, Yiwei Ma, Kaibi Zhang, Luning Lei
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Abstract

In response to the low level of agricultural production automation and labor shortage, to improve the efficiency of agricultural machinery utilization and the reliability of automatic navigation, this paper designs an intelligent agricultural machinery system based on OpenMV for multi-vehicle unmanned following operations. Firstly, the kinematics of the agricultural machinery vehicle is analyzed, the path recognition and location line extraction are carried out using the OpenMV vision module, and the agricultural machinery steering control system is designed using the cascade PID closed-loop control technology, which achieves accurate steering control and path tracking on straight lines and curves. Subsequently, using embedded microcontrollers to manage the workflow, utilizing OpenMV visual modules to receive, store, and process positioning information, and sending control instructions to execution units such as the TB6612FNG motor drive module. Moreover, in response to the communication issues involving multiple HC-05 Bluetooth modules in the system's multi-vehicle communication, corresponding protocol specifications have been developed, and combined with the use of the HC-SR04 ultrasonic module to maintain dual vehicle distance and obstacle detection, achieving multi-vehicle collaborative following operations. The experimental results show that the system achieves a path recognition navigation accuracy of 93.4% and a communication success rate of 97.5% in simulating the process of farm harvesting and transportation, effectively proving the multi-vehicle collaboration of the system in the paper
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基于 OpenMV 的多车无人跟车驾驶系统
针对农业生产自动化水平低和劳动力短缺的现状,为提高农业机械的利用效率和自动导航的可靠性,本文设计了基于OpenMV的多车无人跟车作业智能农机系统。首先,分析了农机车辆的运动学特性,利用 OpenMV 视觉模块进行了路径识别和位置线提取,并采用级联 PID 闭环控制技术设计了农机转向控制系统,实现了对直线和曲线的精确转向控制和路径跟踪。随后,利用嵌入式微控制器管理工作流程,利用 OpenMV 视觉模块接收、存储和处理定位信息,并向 TB6612FNG 电机驱动模块等执行单元发送控制指令。此外,针对系统多车通信中涉及多个 HC-05 蓝牙模块的通信问题,制定了相应的协议规范,并结合使用 HC-SR04 超声波模块保持双车距离和障碍物检测,实现了多车协同跟车作业。实验结果表明,在模拟农场收割和运输过程中,系统的路径识别导航准确率达到 93.4%,通信成功率达到 97.5%,有效证明了本文系统的多车协作能力。
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