The Lego Mindstorm car gives the user an introduction to basic programming and robotics, technologies that are essential to advancements today. Most people don’t have a chance to interact with this type of software, yet familiarity with it can help provide understanding of the importance of technologies in a search for efficient energy and our ecological footprints.
The first experiment involved building the car and learning how the motors worked. My partner and I were given a box full of parts that were to be assembled using a long list of instructions. My partner and I had some difficulties as we were missing some of the parts we needed and had to substitute them with other pieces. This added some time to the process of assembling the robot, which took around 25-30 minutes, but we were able to complete it successfully. Before we even connected the robot to the software used to control it, we already began our lesson in sustainability and ingenuity. We did not give up on the robot, simply because we did not have all the parts we needed to make it function, with the help of Professor Shatz we got creative and replaced the parts with similar pieces! The Lego Mindstorm car looks like this after it was initially assembled.
With a few modifications, including a USB wire to connect the car with the software used to control it, and 2 wires that connect the battery with each of the ports.
After the car was assembled and connected to LabView, we began to experiment with the software. The interface was quite confusing for my partner and I, since neither of us had any experience doing this type of experiment. As we followed some basic instructions to program the car, we learned a few of the basics of what it could do. To make the car go straight, we set the power level to 50, added a command to “go forward”, and selected this to run on All Ports. To make the car go backwards, we did the same process except we changed the command to “go backward”.
Here is our very first program! Exciting.
Slowly, we became more comfortable and acquainted with LabView, programming to increase and decrease the speed of the car, make musical noises, and to drive itself over the table. The next step in the experiment was to program the car to makes left and right turns then drive in a circle. This process was difficult for us to figure out and took much longer to program than it had to program the car to make simple maneuvers.
Our next experiment was to understand the difference between human measures and computer based measures. Human measurements are subject to more error than computer based measures, yet it is important to note that computers are not error-free either. We measured the the wheel rotations, the time it took, and the distance the car travelled, compared our measurements with the measurements provided by the computer. Using those comparisons, we calculated the amount of error between our results and the results provided by LabView.
First we calculated the circumference of the wheel: 5.5cm x π = 1.727 cm = 0.1727 m
Below are the comparisons of the amounts we recorded, compared to the amounts the computer recorded (if the computer provided such data)
Wheel Rotation
| Our Measure | Computer Measure | |
| Rotations Measured | 2 | 1.24 |
| Degrees Measured (degrees) | 721 | 462 |
Time
| Our Measure | |
| Seconds | 1.35 |
| Milliseconds | 1350 |
Distance
| Our Measure | Computer Measure | |
| Distance (meters) | 0.24 | 0.22 |
We then calculated the percentage of error between the distance we measured the car going, and the distance that the computer measured for the three power levels we programmed.
| Power Level | Percentage Error |
| 50 | 7% |
| 75 | 11.5% |
| 100 | 2.8% |
Overall, we found that the percentage of error was not extremely high, meaning that human measurements can be somewhat reliable as estimates. However when we consider sustainability and energy usage, human measures or estimates are not precise enough to provide the answers that are essential to us. Use of computers and software gives us precise answers that can help us understand and predict what actions we need to take in order to conserve energy and be more sustainable in our actions.
I had similar results when it came to the percent difference in the experiment. I like how you connected this lab to us using computers in the real world as a way to help us figure out the best action steps to take.