Abstract
This paper presents the system architecture of a driverless robot car, designed to participate in the Carolo-Cup, a competition regarding automated model vehicles. We describe an implementation that completed the different tasks in this competition on our EyeBot platform in detail. EyeBot has one RGB camera as well as three infrared distance sensors, and it’s powered by Raspberry Pi 3B. We developed the lane detection algorithm using the OpenCV library and completed the traffic sign recognition task based on SVM which can be used offline. Experimental and simulation results recorded in real-time are also reported. The test result showed that our programs can run at high speed to achieve stable motion control in real time and complete all the tasks in the competition. The highlight of our work is that the whole system can run on a platform with limited computing resources.
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