This thesis research proposes a new method for a controlling an agricultural robot using computer vision. The robot has to follow and simultaneously reel in a hose, which lies on a grass field. The hose that has to be followed, is attached to the robot itself. The trajectory of the hose is captured by a monocular camera and is extracted from the image by using a vision pipeline. The vision pipeline consists out of semantic segmenting in combination with a clustering algorithm and polynomial regression to find the trajectory of the hose. This trajectory is used as an input for the PID controller to control the motion of the robot. The presented method of controlling an agricultural robot by using vision control is tested and validated and performs sufficient, when the robot drives with a velocity of 0.2 m/s and when the hose is not partial occluded by long grass.