@@ -75,25 +75,28 @@ We experimented with different angles of the robot when leaning against the door
*Video 3: Calibrating the robot against the door, with a somewhat succesful result (the robot didn't fall over that quickly, but didn't remain standing in one spot either)*
At this point we started wondering whether the wires to the engines were creating a problematic inconsistent weight distribution on the robot, so we tried refitting it, as can be seen in Video 4 and beyond.
At this point we started wondering whether the wires to the engines were creating a problematic inconsistent weight distribution on the robot, so we tried refitting it, as can be seen in Figure 2 below.
*Figure 2: Robot re-designed for better weight distribution.*
#### Testing condition 2: Surface
As we saw no discernible difference with the lights turned on or off, we left it on for the remainder of the experiments as it was vastly easier to work with.
Because we know from past experiences that the measured reflected light for the light sensor is affected by the color of the surface, we suspected that either the color of the bathroom floor, or the inconsistency in the color (as seen in figure 2) could possibly affect the reliability of our balancing robot.
Because we know from past experiences that the measured reflected light for the light sensor is affected by the color of the surface, we suspected that either the color of the bathroom floor, or the inconsistency in the color (as seen in figure 3) could possibly affect the reliability of our balancing robot.
To remedy this, we tried experimenting on a black surface that we dragged into the bathroom, which can be seen in figure 2. A notable problem with this surface, however, was that it was rather rough, and as such could have slightly inconsistent reflection.
To remedy this, we tried experimenting on a black surface that we brought into the bathroom, which can be seen in figure 3. A notable problem with this surface, however, was that it was rather rough, and as such could have slightly inconsistent reflection.
*Figure 2: Black surface in the bathroom, as well as the black and the grey surface next to each other for comparison.*
*Figure 3: Black surface in the bathroom, as well as the black and the grey surface next to each other for comparison.*
As we now couldn't use the door as a means of a solid standpoint for the robot to lean against when calibrating, we now used a box found in the Zuse building instead, as seen in figure 3.
As we now couldn't use the door as a means of a solid standpoint for the robot to lean against when calibrating, we now used a box found in the Zuse building instead, as seen in figure 4.
*Figure 3: Using a box to angle the robot for calibration.*
*Figure 4: Using a box to angle the robot for calibration.*
A problem we discovered with this box was that in some places it was casting a shadow over the surface that we were calibrating the robot on, causing the initial calibration value to differ largely from what it would be once the box was removed. We therefore made a conscious effort to always place the box and robot in a position where the box wasn't shadowing the robot.
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@@ -200,11 +203,11 @@ During the process of switching from the color sensor to the light sensor, the l
*Figure 4: finding the setpoint value in an attempted equilibrium position (first image), start position (second image), and end position (third image)*
*Figure 5: finding the setpoint value in an attempted equilibrium position (first image), start position (second image), and end position (third image)*
*Figure 5: Plot of readings from color sensor (orange) and light sensor (brown), during tilt, along with their setpoints*
*Figure 6: Plot of readings from color sensor (orange) and light sensor (brown), during tilt, along with their setpoints*
The two graphs have about the same shape, with two peaks separated by a valley. The first ~800 ms is the calibration of the setpoint. Then we see the reading values rise as the robot is tilted to its starting position, causing the sensor to get closer and closer to the surface below. After the second peak, we see the reading decrease as the robot is tilted backwards. We are not sure as to the reason for the occurence of the valleys - a guess could be that the robot is lifted slightly from the table again because Camilla, who tilting the robot, was wary of letting the sensor hit the surface too hard (regrettably, we did not make a video recording that includes the calibration of the setpoint and the following move to the start position and so cannot look back and confirm this visually). The different depths of the valleys could be due to the change in lighting level, as described previously.
