This thesis deals with using the gradient descent method for optimizing control parameters of a line following robot. The robot's microcontroller was programmed to operate its control algorithm, as well as search for optimal values of the control parameters using gradient descent. Testing was done on a test track, optimal control parameters were chosen based on the fastest lap-times. Code for the microcontroller was witten in three separate versions with slight variations. Multiple tests on the track were done with each version. After analyzing our data, we can determine that gradient descent is an effective method for optimizing control parameters of a line following robot, since lap-times after optimisation have improved significantly. We have also concluded that choosing good crteria (in this case lap-time) and knowing how control parameters affect each other is very important for effective optimisation.