DRC (Droid Racing Competition)
DRC 2018 - QUT Droid Racing Challenge 2018
The Queensland University of Technology, Brisbane
6 July 2018
Written by Daniel Wong on 07 February 2019
In CREATE’S annual participation in the Queensland University of Technology’s (QUT) Droid Racing Challenge (DRC), we sent two teams to compete against 7 other Australisian universities; Team Cooked and Team Tunnel Vision D.
The competition took one significant change compared to the previous two years. The races were conducted indoors meaning that the effects of glare were significantly less, resulting in overall faster running speeds and fiercer competition.
The day prior, teams were allowed to test and improve their vehicles on the track. Everybody improved their computer vision algorithms whilst making final modifications before the competition.
It was divided into two stages: the heats and the finals. Each vehicle was timed for their travel time around the track whilst evaluated by a panel of judges for overall performance.
During the heats, both teams vehicles dominated the track with exceedingly great results. Team Cooked with a strong start through their flawless drive passing their opponents. Team Tunnel Vision D played a more conservative approach, pulsing their car through the track and consistently pulling through.
When the teams reached the final round however, Team Cooked’s vehicle struggled to find the right path due to a shift in lighting for the indoor arena. Team Tunnel Vision D was also finding it difficult to defeat the now faster opponents. Ultimately, both UNSW teams were pitted against each other in the semi-finals, resulting in Team Cooked placing 3rd and Team Tunnel Vision D taking 4th place.
A huge thank you to all those who made it possible, including QUT for hosting the competition and the UNSW Engineering Faculty for allowing the teams to go on this trip. Congradulations also to the notable opponents from UTS (who positioned 1st) and University of Woolongong (who positioned 2nd).
Both teams learned a lot from this opportunity, including the application of mechatronic principles in programming computer vision with OpenCV, manufacturing and modifying RC car chassis’ and connecting electrical systems to drive the autonomous vehicles.
We thank the partners for their support!
