Due to the pandemic, I was unable to compete in any robotics competition in 2020, which makes this the first robotics competition I took part in. Although I had received training and had attempted numerous practices, none of which was able to be compared with the scale and difficulty of the WRO missions. Needless to say, I had made uncountable mistakes during the preparation for this competition mainly due to my inexperience. For instance, rather than taking my time and brainstorming plausible solutions, I jumped straight into it with my initial idea which I was optimistic about, but after several weeks of testing, I realised that my prototype was not going to cut it. It was difficult to go back to square one and start over but I understood that it was necessary in order for me to have any hopes of improving. This competition taught me the importance of perserverance; to have the urge to continue despite mutliple setbacks which I had faced when the robot was performing inconsistently. It was only after countless hours of hardwork did I managed to overcome these difficulties. In terms of skills, I learnt many new algorithms like PID line tracing, various search and sort algorithms and even implemented depth first search to find the shortest path.

The 2022 mission was radically different from that of 2021. There were many more elements demanding greater expertise in the engineering of robot to enable to it cross obstacles and perform precise actions. Compared to the previous year, the tasks this year were more challenging in terms of building. Upon realising this, I could not help but feel slightly nervous as my building was not as well-rounded as my programming. Nonetheless, I felt that this was a good opportunity to step out of my comfort zone and try out something new and build innovative mechanisms and experiment with different robot bases. Designing a good robot is a multifaceted process that requires understanding in various physics topics such as centre of gravity as well as the principles of moments to enable the robot to perform the tasks with ease, which I felt that I had accomplished. In terms of programming, I was able to design an algorithm to allow the robot to sense objects accurately while moving at high speeds to save time. This led me employ statstics functions like mean and median as well as standard deviation to calculate the optimal sensor reading for evaluation to yield the most reliable results. Furthermore, there were other creative ideas I tried such as using the PID algorithm to control the distance of the robot from the wall rather than for line tracing as there was a lack of lines on the playing field. This method turned out to be very feasible as it was efficacious in maintaining the consistency and positioning of the robot.