SingTown Technology enables robots to "see, walk, and think," maximizing competition performance!

In various robot competitions, recognising track boundary lines is a core capability for robots to achieve automatic tracking, path planning, and steering decisions.
傳統紅外線或單點光電感測器僅能偵測色差，無法辨識線條角度與曲率資訊。
為此，教育機械人製造商採用SingTown的OpenMV智能相機識別技術，整合AI機器視覺與圖像幾何計算演算法，實現對賽道邊界線（如黃灰交界線）的實時識別、角度測量及位置追蹤。
This system can be widely applied in scenarios such as smart car competitions, autonomous driving model cars, and educational programming platforms, providing robots with high-precision visual navigation capabilities.

Educational robot manufacturers utilise SingTown Technology's OpenMV intelligent camera recognition technology to achieve automatic track identification and real-time steering control.

於機械人前端安裝攝像頭，俯瞰地面軌道區域。系統配備電腦視覺及影像識別技術，能夠透過顏色閾值分割、邊緣檢測及線條擬合演算法（霍夫變換）自動提取軌道邊界線（黃灰或黑白分隔線），同時實時計算線條的中心位置與角度。

The recognition algorithm outputs include: the coordinates (x, y) of the line segment's centre point, used to determine the robot's offset relative to the track; and the tilt angle θ, used to calculate the robot's steering direction and correction angle.

當機械人偏離軌道中心或邊界角度突然變化時，系統會立即透過串列埠或I²C介面將位置及角度數據傳送至主控STM32，從而實現轉向修正與速度控制。

The OpenMV embedded vision module maintains stable operation under strong light, shadows, and ground reflection conditions. Leveraging its flexible and efficient on-device AI and edge deployment capabilities, its recognition rate can reach 60fps, enabling true real-time navigation control.

Through this solution, educational robot manufacturers have implemented a machine vision-based track recognition and angle measurement system, enabling robots to "see the track, understand direction, and drive intelligently," significantly enhancing competition performance and intelligent control capabilities.