Kickoff
We attended a local kickoff event with 6 other area teams. We had 30 student team members and 8 mentors attend, which was a great turnout for us. We presented two workshops for local teams, one on outreach and one on drive team preparation.
After the kickoff, we reconvened at our lab space and focused on reading the rules together for Saturday and Sunday. We work in small groups for this, and also do a “World Cafe” discussion style, described in our 2023 build blog. Team members are asked to complete 1678’s rules test.
Our “World Cafe” kickoff notes can be found here
Priorities
With the intention of seeding high and putting ourselves in a position to win an early regional, focusing on the RP task that could be completed with just 2 robots (the trap) was a focus as of Sunday afternoon. Here’s an abridged version of our priorities list:
Task (Kickoff Sunday) |
Should our robot have the ability to do this? |
Climb the chain in center |
Demand |
Climb the chain from side |
Prefer |
^ Climb in Harmony with 1 robot |
Prefer |
Climb in Harmony with 2 robots |
Ignore |
Lift one robot Onstage |
Reevaluate after SMR |
Lift two robots Onstage |
Ignore |
Score with speaker |
Reevaluate after Prototyping |
Score with amp |
Demand |
Score in trap |
Demand |
Floor pickup |
Demand |
Source pickup |
Ignore |
Go under the stage |
Prefer |
Drive over Notes (with high bumpers) or push notes (with low bumpers) |
Demand |
But after some scoring analysis, xRC gameplay, and CAD mockups? We’ve actually re-evaluated this mid-week. We’ve been in a situation in previous seasons where we focused on an RP task to rank high (2016 and 2017), but in those years the RP task at least had a larger point value associated with it. With running some numbers for possible alliance makeups throughout Week 1, it seemed likely that our robot would need to be speaker-capable to really take advantage of the amplification periods and put up enough match points. The trap was a trap (for us).
Task (as of Friday 1/12) |
Should our robot have the ability to do this? |
Climb the chain in center |
Demand |
Climb the chain from side |
Prefer |
^ Climb in Harmony with 1 robot |
Prefer |
Climb in Harmony with 2 robots |
Ignore |
Lift one robot Onstage |
Reevaluate after SMR |
Lift two robots Onstage |
Ignore |
Score with speaker |
Demand |
Score with amp |
Demand |
Score in trap |
Reevaluate after SMR |
Floor pickup |
Demand |
Source pickup |
Ignore |
Go under the stage |
Demand |
Drive over Notes (with high bumpers) or push notes (with low bumpers) |
Demand |
Prototyping
We used our 2023 FRC robot, Larry, to test driving over the 2024 Crescendo game piece. Larry’s drive system is MK4’s from SDS, mounted on the bottom of the frame rails, giving maximum ground clearance. The bumpers sit ~2.25-2.5" above the ground.

We tested a 2-roller intake system for ground pickup. We moved from 2 2” rollers to using a 2” roller and a 1” roller. Yet after further prototyping in order to make the intake system fit the frame of 11.5,” we shortened the lengths of both rollers as well as substituted some of the sushi rolls from the 2” roller with spintakes looking spacers to secure the note upon intake.
Although this slowed this down a tad in comparison to the 2”-1” roller combination, it held onto the note better when it was pulled against while feeding. This was only tested on the lab table top. We were not satisfied with the narrow width roller feed, so we are increasing our intended chassis size from 26” to 28” in order to accommodate a wider intake roller between the swerve modules. We’ve considered the in-bumper setup (shared by team 95), but our CAD team has not attempted this design yet.
We’ve built wooden versions of the field elements in our practice area. One thing worth noting is the spacing on each face of the stage seems sufficient for two large footprint-robots to climb side-by-side. We were able to fit the bumpers for 3 robots across in that space (from two 26” frame size and one 24” frame size robots) but there doesn’t seem to us to be a good reason to put 3 on a chain. Two seems very possible.
We’ve also built a prototype shooter out of compliant wheels (need size) on 2 churros attached to brushless NEO motors spinning in opposite directions. We intended to use CIM motors instead of brushless NEO motors, but the power supply kept saying that one of the CIM motors were getting overloaded before it even moved, so we switched to the brushless NEO motors because they don’t need any code to be controlled, just an app.
CAD
We’ve mocked up several robot design archetypes in CAD with varying levels of detail. We started with trap/amp only designs, but have quickly moved to speaker/amp designs exclusively at the end of week 1. We really liked the Quokka’s Ri3D design, but were looking for an under-bumper solution. We prioritized ways to combine intake and scoring into one mechanism, and to keep everything within the frame perimeter. Our prototype CAD can be found here.
We tried some KrayonCAD with a focus on reaching the amp/trap.
Amp mechanism on elevator
Amp mechanism on jointed arm
Floor intake → scoring on arm
OTB pivot intake to feeder (like Cranberry Alarm Ri3d)
Quokka arm on swerve base:
Ultimately, with some launcher testing and under-bumper intake testing, we want to use a 2 roller under bumper note pickup, with an adjustable ramp/launcher to reach the speaker. We did a little more CAD development on this last concept. We designed a pivot like in the 2022 Everybot design to move the launcher from speaker score configuration to amp score configuration. We can also adjust the launch angle for shots within our wing. When we return to our lab, a high priority will be testing launch angles to hit the speaker from the auto note line and podium.
This design concept gives us some options. We can fix the angle for initial testing and add the pivot for multiple angles as we go through build season. The reach for amp scoring could potentially translate to trap scoring while climbed. We still need to add 2 independently driven climb hooks on either side of this robot. The amp deflector bar geometry is not finalized. We’ll need some additional testing to be sure that it works as part of the full assembly. The ramp will have feeder wheels on top, 2” compliant, mimicking the REV starter-bot design.
For the moment, much of our build has been on hold, though, so there’s a lot more CAD than prototyping. Here in Knoxville, we’ve had a significant snowstorm roll through - about 3x our typically annual snowfall in a short period. We’ve been out of our shop since Saturday and it could be a few more days before we are able to work in-person again. It could mean a full week less of build time before our Week 1 event!
Media
With the season underway, we published a new short-form video about our thoughts on CRESCENDO. Our season timeline has also been finalized and printed, allowing us to see subteam deadlines and project workflows all on one piece of paper:

Here are our 2024 season goals and timeline posters hung around our Scrum board:


Code
We are using YAGSL as our swerve library, and are waiting for the 2024 version so we can get our 2024 drive code up and running. This is our code schedule for the season.
January
- Jan 16, Drive Base Driving
- Jan 19, Auto Taxi Written
- Jan 23, Controller support implemented
- Jan 26, All sensors implemented
February
- Feb 2, All Subsystems operational
- Feb 13, Full Auto support
- Feb 23, All bugs on subsystems squashed and subsystems doing what they should
March
- Mar 1, Clean Successful Autos (up to 4 notes in speaker, centerline steal, amp auto)
Drive Team
Drive team has been focused on early practice with basic robot control drills as well as human player practice.
The first of the two control drills is to focus on precise tracking while in motion. The second drill focuses more on speed and the ability to both traverse a distance and spin at the same time.
Drill #1 Drill #2
For human player practice we quickly put together a basic microphone setup focusing on the correct height, distance, and angle.
An important part of improving is tracking performance. To better help with this we have made spreadsheets that help depict progress and performance. This is especially useful for the task of human players as we are better able to see the chance of spotlighting.

