学习实践

大二阶段——校赛任务

对于这个比赛,一般的同学都只使用红外循迹模块来完成任务,但是我觉得既然特斯拉可以使用纯视觉实现L2级别自动驾驶,我觉得在这次比赛中是否可以使用强大的openMV来实现小车在“道路”上自动行驶,而且可以更好探索发现openMV的新功能(二值化巡线,模板匹配,边缘检测,神经网络等等)。

不仅是软件方面功能的选择,而且对于摄像头安放的高度和角度,外部的光线条件都有很严格的要求。

其中我们使用了选定像素点对于黑色(ROI)的检测,当经过黑线时,会触发那一个像素点,从而可以使flag标志位置一,还可以记录标志位累积触发数。

调试过程

最终效果

Author

wwq136@163.com
I am a junior majoring in Measurement and Control Technology and Instrumentation, with a passion for exploration and innovation. I have participated in various competitions, such as the Electronic Design Competition and Intelligent Vehicle Competition, and have contributed to national innovation projects, including the development of a fruit-picking robot. I possess strong embedded systems skills, working with platforms like STM32, Arduino, Raspberry Pi, and Jetson Nano, alongside proficiency in C/C++ and Python programming. My interests lie in the intersection of robotics and artificial intelligence, particularly in areas like computer vision (CV) and natural language processing (NLP), with a focus on machine learning. I am constantly learning AI-related technologies and exploring ways to integrate them into practical applications, aspiring to develop digital twins incorporating AI. I use Ubuntu 22.04 both on WSL2 for Windows and on my server. Currently, I am preparing for the IELTS, aiming for a 7.0 score, with a current score of 6.5. My future academic goal is to study at a top 50 QS university in Australia, such as UNSW Sydney, the country’s top-ranked university for engineering. Post-graduation, I plan to pursue entrepreneurship, focusing on local AI model deployment, particularly in healthcare. In addition to my technical pursuits, I am fascinated by Western culture, history, and philosophy, and I look forward to returning to Europe to further explore these areas.
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