Lesson-5.markdown

@@ -14,9 +14,9 @@ The goal of this exercise is to test three different sensors and physical robot
 ## Plan
 The plan is to follow the instructions for Lesson 5 [1]. This plan is divided into three parts:
 
-Build the NXTWay robot and test its self-balancing capabilities using a light sensor and PID control.
-Build the NXT Segway with Rider and test its self-balancing capabilities using a color sensor and PID control.
-Use the NXT Segway 
+* Build the NXTWay robot and test its self-balancing capabilities using a light sensor and PID control.
+* Build the NXT Segway with Rider and test its self-balancing capabilities using a color sensor and PID control.
+* Use the NXT Segway with Rider and test self-balancing capabilities using a gyro sensor and alternative control algorithm.
 
 
 ## Exercise 1 
@@ -26,11 +26,11 @@ Self-balancing robot with light sensor
 
 For this exercise we used a LEGO model build according to the description in [2]. Our final model is shown in the following image.
 
-![Robot with light sensor mounted](https://gitlab.au.dk/rene2014/lego/raw/master/Lesson5/Images/LightSensorRobot.JPG)
+![NXTWay robot with light sensor mounted](https://gitlab.au.dk/rene2014/lego/raw/master/Lesson5/Images/LightSensorRobot.JPG)
 
 We know that the surface which the robot is placed on affects the control mechanism and therefore three different materials are tested. These are a blank white table, a wooden table and a carpet floor which is shown in the following image.
 
-![Surfaces which the self-balancing robot is tested on](https://gitlab.au.dk/rene2014/lego/raw/master/Lesson5/Images/LightSensorSurfaces.jpg)
+![Surfaces which the self-balancing NXTWay robot is tested on](https://gitlab.au.dk/rene2014/lego/raw/master/Lesson5/Images/LightSensorSurfaces.jpg)
 
 By inspecting the robots control mechanism we concluded that the best of the three surfaces was the blank white surface and therefore the following tuning and analysis of the PID parameters are performed on this surface.
 We have created a standard PID software architecture which makes the replacement of a sensor easy. The architecture is shown in the following image.
@@ -122,12 +122,23 @@ When the LEGO robot is tilting forward the light sensor will get closer to the s
 ## Exercise 2, Self-balancing robots with color sensor
 
 ### Setup
-The robot was assembled according to [3] with some minor modifications. Since the upright motor is not used in the case of a segway 
+The robot was assembled according to [3] with some minor modifications. Since the upright motor is not used in the case of a segway. An image of the robot is seen in the following image.
+
+![NXT Segway with Rider with light sensor mounted](https://gitlab.au.dk/rene2014/lego/raw/master/Lesson5/Images/ColorSensorRobot.JPG) 
+
+| Parameter     | Value  |
+| ------------- |:------:|
+| Kp            | 7.5 |
+| Ki            | 10 |  
+| Kd            | 2.5 | 
+| Offset        | 480 |
+| Min power     | 80 |
 
 ![Output of the color sensor when performing self-balancing](https://gitlab.au.dk/rene2014/lego/raw/master/Lesson5/Measurement/ColorMeasurements.png)
 
 
-## Exercise 3, Self-balancing robots with gyro sensor
+## Exercise 3
+Self-balancing robots with gyro sensor
 
 ### Setup