In todays class we conducted a robotics activity. This activity allowed us to build our very own robots using Legos! Sounds cool doesnt it? It brought me back to my childhood, when I used to play Legos with my older brothers.Well is wasnt all fun and games the obejective of doing this activity was to study the motion of robots and merasurment of distance and power. Ok now I’m back to reality.
So heres the break down
We calculated our results using some formulas. The set of formulas my classmates and I used all built on top of eachother meaning if you miscalculated one thing the whole calculations would be wrong and you would have to start from scractch.
First we started with measuring diameter of the robot’s tires in order to calculate circumference. We measured using a standard and converted from inches to centimeters to meters.
Here’s the conversion equations:
cm = in • 2.54
m = cm/100
The diameter of the tires equaled 0.0508 m.
From this we calculated circumference using this equation:circumference = π • diameter or C = πd. From this we calculated that C=0.1596. This is the number we input into the computer program for Lego Mindstorm.
We powered on our robots to begin and the math still wasn’t over. With the circumference we needed to figure out number the of wheel turns. For this we had another equation:
Number of Wheel Turns = (rotation°) / (360°/1 Turn)
Then both wheel turns and circumference were used to calculate the distance our robot travelled:
Distance (meters) = Number of Wheel Turns • Circumference
Distance was entered into yet another equation to find velocity:
Velocity = Distance (meters) / Time (seconds)
To begin the actual experiment, we cleared a pathway for the robot to travel without any obstructions (like its power cord which kept getting in the way) and adjusted the power so that the distance would not exceed the measurement of our ruler, 12 inches or 30.48 centimeters or 0.3048 meters.
We conducted a trial of one power level (75) and three sets of testing for increased accuracy. We found that our measurements of distance we never the same and always greater than those measured by the computer. This could be due to eyeballing exact distances when they fell between the marked lines of the ruler. I’ll list our measurements or distance (D) and velocity*(V) compared to those of the computer in addition to number of wheel turns (WT).
*Because in our tests we set time (seconds) = 1, velocity and distance are equivalent in number
Test 1
Students Computer
D = 0.27305 D = 0.227873
V = 0.27305 V = 0.227873
WT = 1.42778
Test 2
Students Computer
D = 0.2795 D = 0.24605
V = 0.2795 V = 0.24605
WT = 1.54167
Test 3
Students Computer
D = 0.27432 D = 0.246493
V = 0.27432 V = 0.246493
WT = 1.54444
At the end of our trial set we calculate our margin of error in order to measure how applicable our results were. A high margin of error means results are less accurate/applicable and a low margin of error means results are more accurate/applicable. To measure this we used this equation:
% Error = ( (Distance measured – Distance calculated by computer) / ((Distance measured + Distance calculated by computer) / (2) ) •100%
The margin of error for each test is detailed below.
Test 1
% Error = ( (0.27305 – 0.227873) / ( (0.27305 + 0.227873) / 2) ) •100%
% Error = ( (0.045177) / ( (0.0500923 / 2) ) • 100%
% Error = ( (0.045177) / (0.2504615) ) • 100%
% Error = 0.18037503 • 100% = 18.04%
Test 2
% Error = ( (0.2795 – 0.24605) / ( (0.2795 + 0.24605) / 2) ) • 100%
% Error = ( (0.03345) / ( (0.52555 / 2) ) • 100%
% Error = ( (0.03345) / (0.262775) ) •100%
% Error = 0.12729521 •100% = 12.73%
Test 3
% Error = ( (0.27432 – 0.246493) / ( (0.27432 + 0.246493) / 2) ) •100%
% Error = ( (0.027827) / ( (0.520813) / 2) ) • 100%
% Error = ( (0.027827) / (0.2604065) ) • 100%
% Error = 0.10685985 •100% = 10.69%
The average for the % error for all three tests is as follows:
Average % Error = (% Error Test 1 + % Error Test 2 + % Error Test 3) / (Total Number of Tests)
Average % Error = (18.04% + 12.73% + 10.69%) / 3
Average % Error = (41.46%) / 3 = 13.82%
I consider Our margin of error resonable taking into account our small sample size.
Over all this lego activity was really cool! It managed to combine fun and learning!
View our master picace aka our robot below:
