Optical camera communication (OCC) is a promising technology for camera-mounted mobile robots (MRs), where it can use its camera to communicate with light-emitting diode (LED) infrastructures. Due to the limited angle of view of current commercial cameras used in MRs, the cameras cannot detect LED everywhere inside an area illuminated by an LED; hence, much of the illumination surface remains unutilized. Herein, we propose an automatic camera inflection algorithm to successfully detect LED anywhere inside an LED cell (the total coverage area illuminated by LED). The inflection mechanism is a supervised learning approach. The technique utilizes the coordinate information (i.e., X and Y coordinates) of an LED cell, which is further employed to track the position of the LED. The coordinate data is automatically updated when the MR travels from one position to another. Furthermore, we perform simulations that include a discussion on tilt angle variation with increasing distance traveled by the MR and a performance analysis that demonstrates the importance and feasibility of the developed algorithm. Finally, a testbed prototype for OCC is implemented to demonstrate the proof of angle measurement theory and bit-error-rate performance of the proposed system.

中文翻译：

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在 OCC 中优化 LED 覆盖率，以便与移动机器人进行有效通信

光学摄像头通信 (OCC) 是一种用于安装摄像头的移动机器人 (MR) 的有前途的技术，它可以使用其摄像头与发光二极管 (LED) 基础设施进行通信。由于目前MR中使用的商用摄像机视角有限，摄像机无法检测到LED照明区域内的所有LED；因此，大部分照明表面仍未得到利用。在此，我们提出了一种自动相机反射算法，以成功检测 LED 单元内任何位置的 LED（LED 照亮的总覆盖区域）。屈折机制是一种监督学习方法。该技术利用 LED 单元的坐标信息（即 X 和 Y 坐标），进一步用于跟踪 LED 的位置。当 MR 从一个位置移动到另一个位置时，坐标数据会自动更新。此外，我们进行了模拟，其中包括对倾斜角随 MR 行进距离增加的变化的讨论，以及证明所开发算法的重要性和可行性的性能分析。最后，实现了 OCC 的测试台原型，以证明所提出系统的角度测量理论和误码率性能。