Observations

## SummaryBoth algorithms were run, individually, with the same controlled variables in place. Each algorithm was to direct a robotic transporter from the docking station to deliver linens to the star area inside the patient room.The following is the path plotted from running the A* algorithm:(Click for larger image)The A* algorithm determined the path above, shown in blue. The robot turned toward the patient room, then navigated closely around the nurses’ station to reach the patient’s room. The pink dotted lines show the accumulated expected variance from the final destination that is caused by the turning action of the robot. I also noticed the following:The robot reached it’s target destination by taking a very direct route to the patient’s room.The robot hit the two corners of the nurses’ station.The robot made 6 turns on the way to the patient’s room.The robot did not realign itself on any walls or landmarks.The robot traveled 15.91 feet in 7 segments.The final expected variance from the target destination is 4.875 feet. That means that the robot could have landed 2.438 feet on either side of the target destination.(Click for larger image)The following is the path plotted from running my accuracy/efficiency balancing algorithm:(Click for larger image)The path (in blue) was developed by my accuracy/efficiency balancing algorithm. The algorithm identified the dark flooring tile straight ahead. It realigned on the flooring tile, then backed up into the wall to alter its direction and straighten itself against the wall. It moved forward and aligned itself on the dark flooring tile near the nurses station. Then, it drove the robot forward to turn around and realign itself on the dark flooring near the doorway of the patient’s room. It then delivered the linens to the target destination in the patient’s room. I also noticed the following:The algorithm caused the robot to take a longer route to the patient’s room verses the route developed by A*.The robot did not hit any corners of the nurses’ station as it passed by.The robot made 5 turns on the way to the patient’s room. This was 1 less turn than that taken by A*.The robot did realign itself 4 times on walls or other landmarks to ensure it was on the correct course. The A* algorithm did not cause the robot to realign itself once. The robot traveled 30.064 feet in 6 segments. A* traveled 15.91 feet in 7 segments. My algorithm caused the robot to travel almost twice as far as the A* algorithm,The final expected variance from the target destination is 3.125. That means that the robot could have landed 1.5625 feet on either side of the ideal destination. The expected variance created by the A* algorithm is 4.875. The difference in the expected variance means that the accuracy/efficiency algorithm had a 36.5% smaller variation than that produced by A*. (Click for larger image)(Click for larger image)

 Observations
Show an understanding of what you saw happening during your experiment. Describe the patterns and trends you saw emerge as you worked.

 Judges' Tip Excellent observations will describe patterns or trends supported by the data (500 words maximum).