Three Years of Progress: How Our Team Evolved Over Time

Lucy C.

Innovation revolves not around perfection but rather around evolution.

Throughout our journey as an FTC robotics team, we have always remained well aware of room to grow and ways to improve. Mistakes have been inevitable, and regardless of how diligently we have worked to reduce error and maximize success, it has been impossible to go a single year without encountering failure and roadblocks. Regardless, we have still remain unfazed by these challenges, using failure as a springboard to learn, grow, and improve. We can never attain that standard of perfection, but we can always discover ways to improve. We can always discover ways to evolve.

Over the past three seasons, CAOS Robotics has sought to learn and grow. Each year we not only made mistakes but also learned from them. Thus we were able to undergo great evolution every season.

Background

Over the past three seasons, we competed in the following games:

Freight Frenzy (2021-2022), a competition where robots were tasked with carrying small boxes and balls called "freight." The freight would then have to be hauled onto a turntable called a "carousel" and a miniature plastic pole containing three large discs called a "shipping hub." The robot we entered into the competition was called Hopes and Dreams.

Powerplay (2022-2023), a competition where robots were tasked with intaking miniature cones and plunging them down small plastic poles called "junctions." Our robot, the Picky Eater, competed during this season.

Centerstage (2023-2024), a STEAM-themed challenge where robots had to compete in various tasks that fused art and science. These tasks included depositing hexagonal plastic pieces called "pixels" onto a blackboard to create 5-pixel patterns called mosaics, launching a paper airplane over a truss, and having our robot hang and suspend itself onto one of the beams of the truss. Gnorp was the robot we entered in this competition.

How our Hardware Evolved

Every year, we were able to enhance and incorporate more functionalities into our hardware. All three robots had mecanum wheels to enable omnidirectional movement and increase friction between the ground and the wheels for easy maneuverability. However, it was only since we designed the Picky Eater that we were able to refine our odometry system: while Hopes and Dreams only had two wheels to track vertical and horizontal motion, Gnorp and the Picky Eater had an additional third wheel to stabilize the robot and track even more motion data. Additionally, while all three robots contained vision software involving USB cameras, Gnorp contained a 3D printed camera mount to ensure consistent angling of our camera so that it could detect our team element and the April Tags that were hung around the field.

How our Software Evolved

The automation of both the Picky Eater and Hopes and Dreams ran on modular programming. This is where a larger program is divided into smaller, independent steps ("modules") that coded for separate tasks. For instance, one module of Hopes and Dreams's automation involved detecting an April tag and depositing a game element nearby, while a separate module controlled when and where the robot parked. Although our modular system allowed us to sequentially and systematically zero in on specific tasks, it would have been inefficient for completing larger, more intricate functionalities, where we have to complete a large, fluid, complex task instead of multiple smaller tasks. For these larger tasks, we would need a method of programming that was more flexible, so we could mold our code to account for all nuances of this single task in one go. This is what we did with the automation of Gnorp! For the first time in our journey with FIRST, we decided to utilize a custom pathfinding scheme to help our robot autonomously move and park without colliding with objects in our playing field. Instead of dividing our pathfinding into a series of disparate modules, we customized a single Bezier spline curve to build the path our robot would move across the field. This algorithm allowed us to better adapt our pathfinding to our playing field in one fell swoop; it was more flexible than a set of rigid modules and arguably more advanced.

How Our Workflow Evolved

When we engineered Hopes and Dreams, we did not utilize a specific work flow methodology or any form of management. Although we were able to receive some mentoring from workers in the STEM industry, we did not have a particular workflow or time management strategy established.

Meanwhile, when we designed the Picky Eater, we primarily relied on the Agile Methodology, especially for our software development. This was a strategy that involved 1) Defining requirements, 2) Planning tasks and time frames to complete these, 3) Developing our design, 4) Testing and implementing the design, and 5) Reviewing and assessing our design's performance. Utilizing the methodology helped hasten the design process, but we occasionally still struggled with delegating and enforcing specific roles for team members to fulfill. This in part contributed to why "...we assigned projects and they kind of fell through," as our former team captain Samson put it. We needed a strategy that not only outlined the steps of our design process but also allowed us to delegate and enforce team roles so that all members could contribute their fair share to each step of our design process.

This was where the power of clever team work and a parallel workflow came in! During our 2023-2024 season, we implemented a parallel system where two robots were designed at once: 1) a starter prototype that could be used as a contingency plan in case Gnorp did not work, and 2) Gnorp itself. Team roles were delegated and enforced accordingly, with our younger team members working on the starter robot and the older team members working on Gnorp. That way, we could divide our workload into manageable chunks that each team member could contribute to, thereby lessening strain on single members and making it easier to accomplish our goals. By dividing the workload and more strongly enforcing team roles, we were able to accomplish both projects!

Our team has demonstrated astounding growth and progress throughout these past three years. Indeed, our team has evolved. While failure and roadblocks are still inevitable, we have nonetheless gotten closer and closer to higher standards of improvement.