Bài báo khoa học

Various machine learning and artificial intelligence applications have gained prominence, propelled by recent technological advancements. Among these applications, autonomous robots stand out as particularly significant. Their integration is anticipated to yield substantial and transformative impacts on society. Current computer vision and deep learning research has been instrumental in developing automated driving systems. Lane-keeping, a critical aspect of autonomous vehicles, has been extensively studied using traditional computer vision techniques and novel deep learning and artificial intelligence models. This study details the design and fabrication of a mobile robot equipped with differential wheels and the development of a PID controller for the robot. It also presents the implementation of OpenCV and CNN models to enable the robot to follow a lane. Experiments were conducted in environments with varying lighting conditions. The experimental results demonstrate the superior effectiveness of the proposed CNN model