Here you will find videographic and auditory evidence of my device's sensor-informed computational and locomotive capacities. Witness these amazing feats with your own eyes!

In preparation for entry into the final competition, I optimized my engine for reliable transport of balls to the goal area. My strategy was as follows: rather than striving to completely eliminate navigational or sensory errors, I attempted to reduce such errors while also making plans for recovery if and when such errors did occur.

For example, if my engine failed to sense the beacon broadcast from the goal it was seeking, it would enter a "searching" mode of operation. This entailed turning in a direction based on the side of the field of competition, then moving forward (closer to the goal, in most likelihood) for a brief period, scanning for the goal all the while. In another example, if the engine failed to align itself precisedly against the desired goal, it would enter a "re-aligning" mode. This entailed moving forward along an S-shaped path for a brief period, then re-attempting to find the correct position.

My numerous error-checking and navigational correction mechanisms served me well, as my Automated Locomotive Computation Engine defeated many esteemed opponents to reach the final round of competition. Gather and watch one such victory!