Robots have revolutionized how we live our lives, they are a technology that has improved our efficiency in even the smallest tasks. Recently in class, we built a lego robot that is programmable to move in any direction and speed that we command it to. Not only is the lego robot able to move in a straight lines, it is able to move along a curved path as well. The lego robot is programmable through a program called labview. Using this program we are able to modify the power that is inputted into the motors, thus dictating it’s speed and direction of travel.
Data:
| Power (w) | Circumference
(m) |
# wheel turns | Measured Distance (m) | Labview Distance
(m) |
Average Distance (m) | Velocity (m/s) | % Error |
| 75 | 0.1696 | 1.544 | 0.274 | 0.262 | 0.268 | 0.274 | 4.477 |
| 100 | 0.1696 | 2.177 | 0.364 | 0.369 | 0.3665 | 0.364 | -1.364 |
| 125 | 0.1696 | 2.114 | 0.365 | 0.359 | 0.362 | 0.365 | 1.657 |
The wheel rotation (in degrees and in number of turns). How are the degrees that the wheel rotated related to the number of turns of the wheel?
The degrees that the wheel turned is equal to the the number of wheel turns multiplied by 360 degrees. This is because one full wheel rotation means the wheel has turned 360 degrees, so: 360 x # of wheel turns = n degrees
The time it took for the wheels to turn (in seconds and milliseconds). How are seconds related to milliseconds?
The time it took the wheels to turn once is equal to the circumference multiplied by the reciprocal of the velocity. So:
Power 75: 0.1696 m x 1/(0.274 m/s) = 0.618 s
Power 100: 0.1696 m x 1/(0.364 m/s) = 0.466 s
Power 125: 0.1696 m x 1/(0.365 m/s) = 0.465 s
1 second is equal to 1000 milliseconds.
The distance the car moved. How is the distance related to the number of turns
For distances refer to table. The distance is the circumference multiplied by the number of wheel turns.
Discrepancies
Also, by measuring the diameter of the wheels of our lego robot, given an allotted time, the program will give a predicted distance travel and average velocity. However, because the robot’s wheels act independently, they are not perfectly in sync; and thus the path followed by the robot is not a perfectly straight line. This leads to discrepancies in the labview calculated distance travel (which assumes a perfectly straight path) versus what we actually measure the distance to be with a ruler. Another possibility for error in the data was the kick back from the robot braking. Every Time the lego robot stopped, the back end of the robot slight rose due to the abrupt stop. That momentum then pushed the robot back, causing it to lose some of it’s travelled distance