Capaldi Emma I
Phillips Academy Andover, Andover, Massachusetts, United States of America.
PeerJ Comput Sci. 2024 Feb 16;10:e1826. doi: 10.7717/peerj-cs.1826. eCollection 2024.
In recent years, inexpensive and easy to use robotics platforms have been incorporated into middle school, high school, and college educational curricula and competitions all over the world. Students have access to advanced microprocessors and sensor systems that engage, educate, and encourage their creativity. In this study, the capabilities of the widely available VEX Robotics System are extended using the wireless ESP-NOW protocol to allow for real-time data logging and to extend the computational capabilities of the system. Specifically, this study presents an open source system that interfaces a VEX V5 microprocessor, an OpenMV camera, and a computer. Images from OpenMV are sent to a computer where object detection algorithms can be run and instructions sent to the VEX V5 microprocessor while system data and sensor readings are sent from the VEX V5 microprocessor to the computer. System performance was evaluated as a function of distance between transmitter and receiver, data packet round trip timing, and object detection using YoloV8. Three sample applications are detailed including the evaluation of a vision-based object sorting machine, a drivetrain trajectory analysis, and a proportional-integral-derivative (PID) control algorithm tuning experiment. It was concluded that the system is well suited for real time object detection tasks and could play an important role in improving robotics education.
近年来，价格低廉且易于使用的机器人平台已被纳入世界各地的中学、高中和大学教育课程及竞赛中。学生们能够使用先进的微处理器和传感器系统，这些系统能够激发、教育并鼓励他们发挥创造力。在本研究中，利用无线ESP-NOW协议扩展了广泛使用的VEX机器人系统的功能，以实现实时数据记录并扩展系统的计算能力。具体而言，本研究提出了一个开源系统，该系统连接了VEX V5微处理器、OpenMV摄像头和一台计算机。来自OpenMV的图像被发送到计算机，在那里可以运行目标检测算法，并将指令发送到VEX V5微处理器，同时系统数据和传感器读数从VEX V5微处理器发送到计算机。系统性能根据发射器和接收器之间的距离、数据包往返时间以及使用YoloV8进行的目标检测来评估。详细介绍了三个示例应用，包括基于视觉的物体分拣机评估、传动系统轨迹分析以及比例积分微分（PID）控制算法调整实验。研究得出结论，该系统非常适合实时目标检测任务，并且在改善机器人教育方面可以发挥重要作用。
