U^2 League Tournamnet SWOT

By Fernando, Nalin, Pavit, Anda, Elm, David, Alyssa, and Nirjha

Following the U^2 Tournament, we conducted a comprehensive SWOT analysis to evaluate progress and identify our next steps. With us barely advancing to Semi-Regionals, this analysis reveals both significant improvements and persistent challenges that will shape our strategy heading into competition.

Strengths

9 Artifact Auto: Refining our autonomous routine from scoring six artifacts to scoring nine artifacts was crucial for our team's advancement. This improvement maximizes pattern points and gives our alliance a strong scoring advantage at the start of every match. In close matches, our nine-artifact autonomous can be the difference.

After implementing our new V4 Rimfire system, we successfully eliminated the unwanted oscillation in our shooter, significantly improving overall stability. This upgrade allowed us to reliably shoot from the back launch zone. By operating from the back launch zone, we avoided congestion in the close launch zone, reducing traffic and defensive pressure. Although our accuracy was slightly lower at this distance and required a longer flywheel acceleration time, there were notable advantages. Most importantly, our human player was positioned closer to our shooting location. This reduced the time required to cycle artifacts, resulting in faster overall cycle times despite the longer spin-up period.

Weaknesses

Limelight issues: Due to intense field lighting, our Limelight Vision camera often struggles to consistently detect the AprilTag on the goal. This interference significantly reduces targeting accuracy and leads to inconsistent scoring. Because our camera is mounted relatively low to the ground, even brief obstructions can disrupt tracking and result in inaccurate shots. Our Limelight camera is currently mounted in a highly exposed position with minimal protection. During a match, an opposing robot collided with ours and struck the camera directly, disconnecting it and leaving us unable to score for the remainder of the match.

Judging: During our 50-slide judging presentation, we rushed through the material, spending less than 10 seconds per slide to finish on time. This pace made it difficult to clearly communicate our narrative, design process, and overall progression. As a result, the judges may not have fully absorbed the depth of our work and the connections between the phases of development. We also lost valuable time transitioning between slides, which further compressed the time available.

Opportunities

Turret Time: A potential turret that uses a limelight to automatically track the goal would help our driver immensely because they wouldn't have to waste time angling Scourpius towards it. Cycle times could decrease significantly. One key challenge will be precise turret control on the codes, but this will simplify autonomous routines by reducing the number of required turns. To make this possible, we’ll need to develop Rimfire V5. This iteration will feature a more compact flywheel design, allowing it to fit within the turret assembly without sacrificing performance, making it a more effective shooter.

Wider intake: Our current channel is too narrow to reliably hold three artifacts, causing the third artifact to occasionally roll out before the robot completes its turn. This inconsistency costs us valuable time and scoring opportunities. Additionally, intaking with the side belt has proven inefficient and unreliable. To address these issues, we plan to widen the intake by 50% and eliminate the side belt entirely, transitioning to a top belt system. This configuration will provide more consistent artifact control and smoother feeding into the shooter, especially since we plan on incorporating a turret.

Back side auton: With Rimfire V4 giving us the capability to shoot from the back launch zone, it’s crucial that we develop an auton to take advantage of it. To remain versatile and maximize scoring potential, we should have both front-side and back-side autonomous modes. This allows us to adapt to different match strategies and alliances. Ideally, this auton would score nine artifacts, including the three preloaded artifacts.

Some penalties can have a huge impact on a match. During the DECODE season, fouls can quickly add up and cost the team valuable points. With our limited driver practice time, it’s especially important that we thoroughly review the rules. Our human player also needs to actively watch for potential fouls and communicate them clearly to the driver in order to help us avoid penalties and maximize our scoring opportunities.

Threats

Our biggest threat is highly efficient teams that use a turret system. We’ve addressed most of the challenges we identified at league meets, such as the contested launch zone in the front, by adapting our strategy to shoot from the back zone instead. However, we now have to compete with teams that have fast, efficient intakes and very low cycle times. Improving our driver consistency and continuing a robot redesign will be key to staying competitive and performing at a high level.

With our work cut out for semi-regionals and our funding fully secured, we launched a Fund the Run to Regionals: 2-Week Sprint for Teams 3734 & 6832, where every donation will support robot changes over those 2 weeks. We will use what we learned through our SWOT to hopefully make great strides and be in a better position for Semi-Regionals.