This paper presents the implementation of a crack tracking mobile robot. The crack tracking robot is built for tracking cracks on the pavement. To track cracks, crack must be detected by laser and camera sensors. Laser sensor projects laser on the pavement to detect the discontinuity on the surface and the camera captures the image to find the crack position. Then the robot is commanded to follow the crack. To detect crack position correctly, neural network is used to minimize the positional errors of the captured crack position obtained by transformation from 2 dimensional images to 3 dimensional images.