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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.

Optimum LED coverage utilization in OCC for effective communication with mobile robot