lesson-4.md

@@ -128,8 +128,11 @@ After implementing this, our robot seemed more responsive to the black line but
 ##### Integrating to correct behaviour given history and using derivative to predict future state #####
 By integrating from an amount of previous samples, the application can classify its situation better, which allows the program to follow the line more closely. By taking the derivative of the last two error measures, we can also predict future states better.
 
-We played around with this ....
-SNAK OM DE TRE VÆRDIER, INDSÆT EN MASSE FILM
+As we didn't have any solution of how to set the values in our application for proportional (Kp), integral (Ki), differential (Kd) and base motor power (Tp), we experimented with the values until we had a solution where the robot both drove with a somewhat fast speed and where the movement was fluid on straight lines as well as during turns.
+
+![PI](/uploads/8f581487fd1e89f0c3ae6fae85bbd4b5/PI.mov)
+*Figure X: The video shows the robot fluidly driving around a circular track following a black line on white surface.
+
 
 ### Color Sensor ###
 
@@ -186,7 +189,9 @@ Is it possible to use the color sensor for both following the black line and sto
 #### Execution ####
 
 ## Conclusion ##
-This is not the conclusion your looking for!!!!
+During these exercises, we have learnt that a robot can be fitted with multiple sensors to complete the same tasks with matching behaviour. Other than the basic light sensor, other sensors can be used to check for end zones indicated by other colors due to some sensors abilities to register other colors.
+
+While a simple program fitted with an advanced sensor can fulfil some goals, more advanced behaviour requires advanced applications. We have delved into this by implementing a PID controller into the application, such that the robot moved with less jagged movement than without the PID controller.
 
 ## References ##