Track: High School STEM Project Presentation

Abstract

Self-driving car performance is of great research interests these days. We would like to use a LEGO EV3 robot to simulate a Google self-driving taxi that is on the way to pick up five chief speakers to the conference center on time. Our major focus is on how to improve the route tracking accuracy and the cycle speed. Team has designed a very challenging field to test how the Robot could overcome the sharp turns at faster speed.  Team measured the optics contrast to determine the measurement signal-noise ratio as the fundamental quality statistics. We can optimize the Robot performance by measuring the optical contrast.  Based on SPSS Histogram analysis, team has distinguished several Robot movement patterns associated with each distribution peak/mode.  Team was able to conduct further root cause analysis accordingly to further improve Robot Architecture Mechanics, EV3 Software Programming, and control the environmental light variations.  Each Histogram distribution mode has indicated a unique robot movement failure mode.  Team can apply statistics on a very complicated Robot Mechanics, Physics, Optics, and Software Programming like an experienced Robotics Engineer through Team Building. Team has optimized these critical parameters in order to make this Google Taxi service safer and faster.