FRC 1757 Wolverines 2022-2023 Build Thread

Hey all-

Welcome to Team 1757’s first build thread! We will be sharing frequent updates regarding our 2022-2023 season here.

Who are we

Founded in 2006, we are a high-school robotics team from Westwood, MA and compete in the New England district. With three lead mentors and twenty active members, we are a relatively small team and mainly student run. We aim to improve access to STEAM and further develop the team in terms of leadership, innovation, communication, and self-confidence.

Our team is divided into two main branches: technical (anything to do with the robot which includes programming, design, and mechanical) and business (areas that do not deal with the mechanics of the robot which include media, outreach, graphic design, and finance).

Currently, our preseason schedule includes meetings in a variety of areas. Sunday mornings are for in-person mechanical meetings. Mondays consist of an after school meeting for robot-specific programming followed by Python classes online. Tuesdays have biweekly outreach meetings. Wednesdays consist of after school CAD meetings followed by a technical meeting online. And finally, Thursdays consist of online CAD classes and business meetings afterschool.

2021-2022 Robot Reflections

Coming into the 2021-2022 season, we decided to change our approach in certain technical areas. For the first time we created a complex robot using python, despite the lack of official support. This choice of programming language proved to be beneficial as programming became more accessible to the team. We spent less time learning the language and more time refining our algorithms.

We also fully designed our robot in OnShape, which allowed us to plan everything out exactly how we wanted and give the programming subteam a head start before the bot was fully built. Because the model accounted for every part and dimension, things like weight and perimeter, restrictions were no problem during the building phase. These massive pre-season changes set the team off on the right foot.

Additionally, there were many other factors that contributed to our great performance last season, especially regarding individual subsystems.


Last year was our first year using swerve drive, SDS Mk4is, and they helped immensely as a functional drive base that could be built off of in programming. The code of the autonomous sequence was a bit patchy, but we managed to get it working for a five ball autonomous sequence. The new autonomous code used pathplannerlib instead of traditional wpilib trajectories, which was more reliable in regards to rotation. Absolute relative drive minimized driver thinking by having field relative translation and complete joystick controlled absolute rotation. Further, we developed a moving shot with our turret (although limited to forward and backwards motion). To combat defense robots, we used an X-wheel anti-defense mechanism with our swerve drive.


While initially lacking in capability at Revere, only being able to shoot at a set speed and angle, it soon after became the impressive part of our robot. Our turret is able to rotate with 320 degrees of freedom, adjust its hood, and use a limelight to track the upper hub to discern the robot’s distance and angle from the goal. With this information, the turret is able to follow the target when the beam-break sensors detect a ball, adjusting flywheel speed and hood angle to gain a greater than 80% consistent upper hub shot with a varying position. In the event of no good vision information, our robot uses odometry estimations from our swerve drive in combination with our recorded distances and angles from our vision system to approximate where we are on the field to then orient and use just the limelight.


The indexer had the least revision besides the swerve drives, only needing one minor change to make the final bot. It operates using two motors, one near the intake to collect incoming cargo, and another near the shooter to pass it on and out. It also includes two break beam sensors positioned to detect held cargo. The sensor closer to the turret turns off the limelight when cargo is not present and also stops the turret from rotating, to prevent any possible misinformation when not needed. Further, when we have two balls inside this subsystem, we turn if off to save battery usage. As a subsystem, the indexer has been very reliable and never failed us in competition due to its simplicity.


We’ve made the most revisions on the intake system. It did pose some issues: the early plates were not thick enough (in WPI elims our intake stack broke completely twice) and the belts have been falling off. Nevertheless, the system was still highly effective as we were able to properly test it using our offseason swerve bot. In retrospect there wasn’t much reason to have it be pneumatic because we likely could’ve saved weight with a fully motorized intake, and also not run out of air during the end of matches


The climber subsystem was the biggest struggle for us: it was over engineered, heavy, and easily broke. We didn’t properly consider many aspects of the cylinders; therefore, they broke and interfered with turret movement, intake, and vision. When they did work, we consistently got a mid bar (and likely low bar) climb for last minute points for RPs. Ultimately, towards the end of competition season, we would continue to shoot cargo while other more competent bots were climbing because that was a much more guaranteed source of points rather than putting our hope in the climber.


Our first competition was the New England District Greater Boston Event, ranking us 24th out of 37. We had a very rough start, but as the competition progressed, we fixed most of our bugs, and our improved performance landed us as the 2nd pick of the 6th alliance.

WPI was our second competition of the year, and we fared a lot better this time. Our turret saw the most improvement, being able to score 20+ balls by ourselves: we enabled the ability to track the target with vision, improved the turret’s range or rotation, and fine-tuned our shots. By the end, we were 6th in terms of OPR. We were ultimately disappointed by our early exit in the knockout stage, but our improvement was a good sign. Additionally, the turret and control scheme granted us the Innovation in Control Award, our first technical award since our rookie year in 2006. The combination of the award and our improved performance at WPI was enough to grant ourselves a ticket to Districts Championships for the first time since 2017.

The New England District Championship was our best competition. Everything that went well at WPI went well here as well, and our turret accuracy landed our bot 6th in terms of OPR. Additionally, we earned another award for our efforts, the Quality Award, and we finished 17th out of 40 teams in the Calcium Division. We managed to drag our knockout round draw into the 3rd match, however, we ultimately couldn’t progress past the quarterfinals. We surpassed our expectations and exited the Colisseum with our heads held high, hopeful that, for next season, we could capitalize on our increasing confidence and momentum.

We Were a Statistical Outlier

If not already readily apparent from our discussion we believe its worth noting that we were very much a statistical outlier in the NE district. While our OPR was extremely high, all of our points came from CARGO and not HANGER points as shown in the bar graph above. Its just a reminder that do dont always have to build an every bot, if you can find one aspect of the game that you can do as good or better than everyone else you can make your team just as successful as others who may have more time or resources to devote to perfecting every system on their bot.


The team had restarted due to COVID 19, not taking part in the 2021 virtual season. This left very few veteran members, and we spent the first few months redeveloping our entire team from scratch. Our business team was only managed by two team members, greatly limiting our fundraising and outreach potential. Furthermore, in the absence of the school’s annual in-person club fair, our member recruitment and retention levels were low. However, we took advantage of the pandemic model and began online classes to train new members. This adjustment was especially effective in improving team connectivity.

Our goals for the upcoming season involve continued recruitment and retention, which includes bringing new members to offseason competitions and increased team connectivity. Further, we aim to begin recruitment of new members in the spring rather than in the fall, so that we may utilize the summer to train up new members. We are also aiming to create a larger business team, thus improving our outreach and fundraising capabilities.

We hope you found our experiences informative and helpful. In case you have any questions about our robot, team, organization or more, feel free to to contact us! We anticipate sharing more about our advancements as we move closer to build season.

Best Wishes,
1757 Wolverines


Website -
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GitHub - Westwood Robotics · GitHub
CAD - Onshape

Written by Sean, Baili, Claire, Nolan, Luke, Divya, Ivan, and Steven (mentor)


Is there anything mechanically speaking you are looking to change this year vs previous years?

There is always things you wish you could fix in retrospect. Our primary mechanical takeaways from this year are to do a better job protecting drive belts from falling/flying off their pullies, and more CNC/3D printed parts as we expand our capabilities in both of those areas


Could you share a little more about the climbers you developed? It looked like a very compact solution reminiscent of some of the tiny robots of 2021. Very curious what the solution looked like since we didn’t get a chance to compete much with you guys this year.

They were mostly an off shelf solution WCP climbers (GreyT Telescope – WestCoast Products) with the hooks from the Andymark Climber in a box (Climber in a Box - AndyMark, Inc )
We wanted to keep the climbers under the height of our turret so that the turret could aim freely so we had to increase the # of stages but lower the length of each stage. In CAD everything worked out perfectly, but like all things, when put in practice, it was another story. the arms were actuated forward and backward by two beefy short-throw air cylinders. As you can see from the image below the Cylnders cast aluminum housing couldn’t withstand the sideload


Am I blind or is there no graph?

Currently I’m limited by the “New Member” trust level, I’ll add those in when that expires.

Here are the graphs in question:


I’m going to add something that wasn’t mentioned in the original post by Sean but I feel is mechanically relevant for a recap.

Instead of using a traditional gear setup for a hood, we use a CAM shaft deflecting polycarb. This allows for all the angle adjustment necessary and reduces complexity on our shooter. The added downside is it results in no backspin compensation, but through proper mapping of speed and angle the backspin doesn’t affect our shot accuracy.



Preseason Updates (Aug-Oct)

During our offseason, we explored ways to resolve some of the team’s mechanical and organizational bottlenecks. Today’s update will summarize our purchase of an Omio X8 CNC Router to expedite part construction as well as new member recruitment strategies to ensure team sustainability.

Offseason Project: Our Omio X8 CNC Router

Last season, we made good use of a handheld Shaper Origin router to cut many of our robot parts. The router helped produce clean parts and was easy to use; however, it required a team member to be using it at all times. Manufacturing parts with this singular router was time consuming and bottlenecked robot construction. We had to manually adjust our feeds and speeds depending on the material and thickness of the stock (for example, the construction of our indexer took over 12+ hours, between the Lexan and metal portions).

Now, we’re taking another step in this direction with our new Omio X8 CNC Router. Using OnShape to design a part and Kiri:Moto to generate G-Code, we found success with our test cuts. Initially, we were unable to set up the router due to the WCP skin not containing the necessary information and buttons, so we reverted to the default interface. We had an issue with unit conversion where the software G-Code and machine mixed up inches and millimeters, which we fixed by changing both our generated and the software’s G-Code to work exclusively in inches. After this, we successfully cut some small parts out of wood and aluminum with the feeds and speeds listed below.

Aluminum (¼” bit):

  • Spindle Speed: 18000 rpm
  • Feed Rate: 55 ipm
  • Plunge Rate: 2 ipm

Wood (¼” bit):

  • Spindle Speed: 14000 rpm
  • Feed Rate: 70 ipm
  • Plunge Rate: 2 ipm

We plan to research more and experiment with our feeds and speeds, as well as try cutting with polycarbonate in the future.

Some pictures

In order to house the router in our limited school space, we designed an enclosure for it. Our goals were to provide a safe, portable, and accessible home for our new machining equipment. We chose to use 80/20 beams to construct the frame of the cart and lexan panels to provide visibility into it. Another choice included bifold doors as these take up less space and are more versatile than traditional doors. One blunder when designing the cart was using a CAD model (of the CNC) that was 8 in. too short. This caused the top of our cart to be too short, and we are in the process of ordering new material to resolve this. Here is the CAD of our cart and below is a picture of it:

Resolving Organizational Hurdles

One of the main problems we had last year was member recruitment and retention. There weren’t a lot of people on the team to begin with, and as the year progressed, fewer and fewer people remained active. To combat this issue, we first showcased our work and accomplishments to pique the interest of potential new members: we displayed our t-shirt cannon at the freshmen orientation and also exhibited the team to other grades during the school’s club fair, which led to an addition of over 30 new recruits. To address our limited time and low retention rates, we decided to implement off-season lessons to teach new members design, programming, and media principles. On Monday and Thursday evenings we have foundational CAD and programming lessons, and after school on Mondays and Wednesdays we teach the applications of these skills to the robot. Currently, this method seems to be effective based on the team’s performance at NERD and interest in the lessons. We are also currently looking to start elementary minicourses at our local library and promote STEAM to younger groups later on in the year. Moving forward, we hope to expand our outreach further by including more underrepresented groups and increasing community awareness.

Team Pictures


With new machining equipment such as the CNC Router and our increased outreach, we hope to grow as a team in all aspects. We will continue to update our pre-season growth and progress. As always, if you have any questions please feel free to contact us!

Best Wishes,

Team 1757

Written by Claire, Divya, Anthony, Ivan, Luke, and Sean


Offseason Competition: N.E.R.D

The N.E.R.D competition was a huge success. It is the first off-season competition we have participated in since 2014, and we performed very well, placing as the second-seed team and reaching the finals during eliminations. We were able to test out our new scouting system as well as a few robot changes. The competition allowed us to provide a glimpse of the season to our newest members and foster team bonding. Check out our recap here!

New Scouting System

Previously, our scouting system consisted of filling out a Google Form over and over again and switching between counters and the Google Form on our phones. This method made our data wildly variant and disorganized, which was very confusing for our team. To combat these issues, we created a scouting system (credit to Luke for creating it in his spare time) for the upcoming season using NodeJS. We chose to use NodeJS for the server because of its extensive community and industrial support. For the front end, Svelte was used as a rendering framework because it was nice to work with, reduced total network usage on the end use, and facilitated traffic; this would be especially useful during competitions when at least 10 people will be using it at the same time. The backend uses expressJS because of its wide commercial documentation and assistance to support the programs. Of course, human error will still be present, but this will be offset by data pulled from TBA.

Our new scouting system is designed to provide organized, accessible, and comprehensive team data for match strategies. Scouts record how each bot performs during the autonomous and teleop phases as well as its hangar performance. The main page consists of all the data on each team, displaying their performance across all their matches, including score, shot accuracy, and average cycles. Moreover, we can analyze data from past competitions or filter it to provide recent match data.

Match info includes predicted score, and if the match has already been scouted, it includes a score breakdown for robot contributions within an alliance. To predict scores, the app averages past climb and cargo scores, assuming that the robot will perform similarly. This accumulation of information in our database allows us to have a better picture of a match and its conditions.

Aside from the quantitative data, qualitative notes are also critical in scouting and planning in terms of understanding different teams’ strengths and functionality. Scouts are to record their observations: for example, they can note whether the bot was dead on the field, played defense, experienced mechanical issues, or other important observations. Furthermore, the lead scout has the responsibility of forming match strategy and determining overall bot function at any time. The notes they take are qualitative and independent from other observations. These notes are crucial when selecting alliances.

Additionally, we had an on-field bot analyst make qualitative observations on various teams before the competition. The lack of matches meant incomplete scouting data; thus, this ensured that we could rely on a strong and thorough database.

Robot Changes


Over the season, we updated the odometry so that it was determined by the turret angle and limelight readings, in addition to the movement of the swerves which it was based on originally. To prevent the limelight from setting the odometry incorrectly while in the hanger or other areas, it remains off until the indexer holds a ball. Following this, we decided it was advantageous to shoot based on the odometry because it provided the turret with a smoother transition, eliminating the limelight noise which often factored into the turret’s aiming. Since the limelight information is weighted into the odometry calculations, the robot has a sufficient approximation of the hub’s position and isn’t required to use the limelight’s pure data.

A big reason for our success was our ability to quickly pick up balls and shoot them into the upper hub, so we decided to have our hood angle and flywheel speed change based on odometry rather than the limelight. This prevents the current from spiking when the target suddenly comes within vision, as well as reducing the time needed for the shooter to adjust before shooting.

Shooting changes

In order to further improve our shooting efficiency, our next step was to implement a moving shot so that we could score and simultaneously move towards additional cargo. Unfortunately, It was only effective when moving directly to and from the hub. Given more time, we would have liked to make it work with a wider range of motion. However, this was a feature we didn’t put to much use during N.E.R.D for the sake of reliability.

During the competition season, we used Pathplanner to export json files which then had a basic wrapper to extract the data. This data was filtered through a custom function that translates it into instructions for robot movement. The autonomous routines didn’t change much for N.E.R.D, but PathPlanner in RobotPy released official ways to extract the data that it creates. With this change, along with the updates to odometry, our autos were more accurate than ever. Due to a lack of time to fine-tune the path, the robot frequently missed the ball in front of the terminal; however, the other balls made it into the upper hub.


If you were at N.E.R.D. or watched our match videos, you may have noticed that we added LEDs to our robot. We added LEDs to the robot not only because they looked cool, but they also reduced the mental load of the drivers by providing an easy way to check the status of the ball storage and shooter. Each color represents a different state, changing when the indexer holds one, two, or no balls, and when the shooter is on or off target. The distinction between on and off target is separated into warm and cool colors in order to discern at first glance when the robot is ready to shoot.

Red - No Ball

Yellow - 1 Ball No Target

Magenta- 2 Ball No Target

Blue - 1 Ball On Target

Green - 2 Ball On Target

Rainbow - Disabled

These lights also indicated when the robot was booted up, helping the drive team on-field as well.



Despite our great performance at N.E.R.D, there were still a couple of road bumps. During the entire competition, the gyro was drifting, which increased difficulty in controlling the bot by altering driver-centric translation and absolute rotation. Furthermore, at the beginning of the event, the FMS system failed: all play was halted, and a two-hour intermission was taken. We also lost communication with the robot for 10 seconds during one of our rounds. That lost time was critical because that round ended with a tie, and the disconnection cost us the match because we had more penalties than the other team. In the finals, the bot’s intake belt fell off twice. This prevented us from being able to pick up balls, contributing to our loss in the finals.


We were able to place second overall in the event; we did quite well throughout the competition despite some technical difficulties near the end. We were ranked second seed during alliance selections and eventually became a finalist during eliminations. These achievements are significant for us because this is the first time we have ever made it to the finals in team history.

Overall, we had a lot of fun at N.E.R.D! It was a great opportunity to develop team spirit and bond with each other. It was also many students’ first competition, so they were able to get a first glimpse of the upcoming season. Additionally, we tried out our new scouting system, tested some robot changes, and our media team had a chance to shine! Check out the photos below!


We will continue to update our pre-season growth and progress. As always, if you have any questions please feel free to contact us!

Best Wishes,
Team 1757

Written by Anthony, Baili, Claire, Landon, Ivan, Adrian, Divya, Sean, and Luke


Preseason Updates (Nov) and Our T-Shirt Cannon!

Over the past few weeks, we have been working on our CNC Router, T-Shirt cannon, and a Mk4i swerve base. We have taken time this preseason to experiment with new machinery and robot mechanisms. Our team also aims to gain experience with our router so that it will save us valuable fabrication time this winter. Additionally, we look to continue community outreach and engagement of underrepresented groups.

T-shirt Cannon

Ever since 2010, our team has built five T-shirt cannons for use at community events and at Westwood High School’s annual pre-Thanksgiving Break Pep Rally. Similar to our competition bot, we connect to our T-Shirt cannon through a router over WiFi. We use DriverStation to control the cannon, which we have hooked up to two controllers. One joystick controls the directional movement, while the other controls rotation.

At its simplest, it consists of a swerve drive with Mk4 modules, which were initially upgraded from Mk3s. On top is the cannon, along with other pneumatics and tubing as well as some electronics. The majority of the electronics are located beneath the cannon board. The T-Shirt uses a 1 gallon tank for main air storage and a smaller firing tank as a working shot. There are two solenoids in the system: one between the main air tank and firing tank as well as one between the firing tank and the “cannon” (see diagram). Various blow over valves and dump valves, staged between solenoids, ensure that the T-Shirt Cannon does not reach dangerous air pressure.

The T-Shirt cannon operates as a state machine with four states: venting, firing, filling, and closed. When both solenoids are activated, air is free to flow from the compressor directly to the cannon, thus “venting” the air in the system. We do not use this state, but it is a possible configuration. When the robot is in a “firing” state, the solenoid connecting the firing tank to the cannon is open, allowing for high pressure air to shoot the t-shirt. Similarly, if the solenoid connecting the firing tank to the cannon is closed while the solenoid connecting the main tank to the firing tank is open, we consider that as a “filling” state. When both solenoids are closed, the T-shirt cannon is in a “closed” state, meaning no air exits or enters the firing tank. The default is the closed state, but the robot will transition to firing or filling when a button on the controller is pressed.

This month, the technical team continued to improve the T-shirt cannon, and one of the notable changes was a swap from Falcons to NEOs. This was a somewhat difficult change and required a few hours to complete. We also added a second air compressor on the bot. This will allow us to reach desired tank pressure (120 PSI) much faster. In order to address the additional current resulting from this addition, we put both compressors on a relay as the CTRE PCM does not accept high current. We cut mounts for the SPARK MAX motor controllers that we added to the robot (as we switched from Falcons to NEOs). We also rewrote the OperatorInterface to match that of our competition bot and made small code adjustments to account for the new motors.

We had a very successful pep rally, despite some hiccups due to signal distance! Check out this video and the rest of our media:


CNC Router Updates

Figuring out how to operate the CNC Router properly was a task, to say the least, but we have been able to cut a few basic parts out of metal. We are still figuring out the most optimal feed rates and spindle speeds (and have unfortunately snapped a bit in the process due to too high of a feed rate). We have also worked on our tread templates to allow for an easier time cutting holes in parts. Specifically, there are two aluminum plates that clamp down on the tread and a ¼ inch polycarbonate plate to hold the tread (pre-cut to length) on the inside. There are hole guides with steel drill guides to make the drilling easy. We made this part because the replacement treads proved to be an annoyance to manufacture, and this would both speed up the process and make it more consistent.

We used Onshape to design it (as always), and used Kiri:Moto as an Onshape plugin to generate the G-code. Although it is convenient, Kiri:Moto has not been as versatile as we would like and we are looking into other options for CAM software (mainly Fusion 360). Once we optimize the router, it will drastically cut down the time we would have to physically cut parts ourselves, instead reserving our time on more integral parts of bot construction.


Drive Base/Competition Robot Changes

We recently made some new developments on our swerve drive base from standard Mk4 swerve modules to Mk4i modules. The motors are now more protected from damage, as they are mounted within the module enclosure rather than above.

Outreach Activities for the Future

We are planning to organize some STEAM classes to expand our outreach. In January, we are planning to offer STEAM programs at our local library (Jan 6th-27th) and coding classes for young girls at a local elementary school (Jan 9th- March 20th). In this, we can inspire more youths and help them pursue their STEAM endeavors. The current curriculum has not been fully fleshed out yet, but the dates are set.


With new developments on the router and bot as well as future outreach plans, we hope to further grow as a team. We will continue to update progress, and as always, if you have any questions please feel free to contact us!

Best wishes,
Team 1757

Written by Claire, Sean, Baili, Adrian, Divya, Rachel, Luke, and Landon


Super excited to follow this thread. I had a chance to meet your team at DCMP and was insanely impressed. I can see 1757 being a powerhouse up here. Best of luck!


Short update (shorter than usual, likely a longer update later)

We did a couple of notable events recently that should be highlighted.

CNC Success
After all this time, we finally experimented with using our CNC router for cutting 2x1 extrusions, after doing so the entire team was relieved at the speed and ease of the process compared to the shaper origin being used previously.
we plane to use these heavy lightened parts for side beams like on our 2022 robot

Community outreach
Last Saturday, we volunteered at a moderately local library wrapping gifts for the holiday season for free. We got a decent amount of people who wanted their gifts wrapped and they were very thankful for our service.

Oh no! its code!
Our programming team is slowly starting to prepare the codebase, currently this is trimming down the 2022 code base for the necessary parts. Since we anticipate using swerve in Charged Up, we are keeping our offseason changed to our drive mentioned in our NERD post. The programming team is also actively updating to meet the new changed within 2023 wpilib and 2023 robotpy.

Happy Preseason,
Team 1757

Written by Luke


Final Post before Kickoff!

With kickoff tomorrow it’s time to update everyone on the last minute preparations in the Lab. Over the past few weeks, we have been working on various projects involving experimentation with new machinery and robot mechanisms. We also need to gain more experience with our router to save ourselves valuable fabrication time this winter. Additionally, we look to continue community outreach and engagement of underrepresented groups.

Mechanical Updates

In our final Sunday mechanical meeting before winter break and kickoff, we looked to replace the swerve treads on our competition robot and T-shirt cannon by using our CNC router. After we corrected the tube fixture on the CNC router, we created a template that allowed for efficient and accurate cuts with the drill bit. We were then able to precisely cut complex patterns, which were created beforehand with Kiri:Moto on Onshape. Kiri:Moto has shown its weakness in being a newer product compared to Fusion360 and other CAM software; however, we were able to work around some of the issues with a couple quick and dirty fixes. For example, complex parts must be cut using the Trace feature, which is tedious to use but works fairly well; however, it has some issues selecting cuts on parts designed in three dimensions. The easy solution in this case was to trim the part into a single face that is cut (pictures attached). For these aluminum parts, we used a ⅛” single flute cutter at 18000 rpm, feed rate of 22 ipm (we broke a bit and were being very careful), plunge rate of 3 ipm, and a pass depth of .075 in. All of these settings are very clocked back but gave a clean cut and didn’t seem to cause issues with heat buildup. When building the templates, we realized that there was unequal load distribution onto the template, and they were not securely in place. This resulted in a couple of imprecise treads. Both our demo and 2022 competition robot have their treads replaced.



We also started work on the battery cart, based on Team 33 “Killer Bees” design. It’s going to house the batteries at both competition and in the lab.

Outreach Updates

On Saturday 12/10 we volunteered for An Unlikely Story in Plainville to offer free gift wrapping. This was an excellent opportunity for our team to connect with the community and we were able to help many people take care of their gift giving stress. With the holidays just around the corner we were glad to help take one more item off people’s to do list.

Additionally, our FLL Team (Tiny Turtles), which we have been mentoring since September, made it to Massachusetts State Championships!! We could not be more proud of their progress.

We have also finalized our curriculum for She Can STEM and our library minicourses, which we are greatly looking forward to starting over the next few weeks!


That’s a wrap on what was our most productive FRC offseason in team history. We hope you have enjoyed our updates so far and can’t wait for Kickoff tomorrow. We are anticipating the best FRC season ever and hope the same for our fellow FRC teams. We will continue to update you all on our progress in this thread, and as always, if you have any questions please feel free to contact us!

Best wishes,

Team 1757

Written by Claire, Luke, Sean, Landon, Baili, Adrian, Divya, and Ivan

Edited by Steve


need to have a Walpole & Westwood team night, order some pizza’s and watch Robots (hope we both make many trips to each others shop’s) hopefully not for missing parts though

1 Like

That sounds like a perfect competition week 0 or week 1 event

Kickoff Season Update!

As the season officially begins, we have started brainstorming our initial ideas and strategies. We analyzed the scoring and rules (especially regarding how much time it takes to do each type of scoring) to figure out what robot skills we should focus on. We have based our game breakdown around team 125’s talk, and our analysis is documented in this spreadsheet, which will be updated during the next couple of days.

Here are a few key takeaways that we immediately identified:

  • Because there is no restriction to prevent the viability of a swerve drive, we will be using swerve due to success and experience. To combat sliding on the charging station, we will likely lock the wheels into an “X” formation once balanced.
  • Floor intake will likely be more manageable than taking from the loading station for scoring points, due to the additional time required to reach the piece.
  • There are a variety of autonomous routines that would all be applicable, such as a 1 game piece, 2 game piece, and 3 game piece routine.
  • Based on our initial time based estimates, placing game pieces on the top row first may yield the most points. However, this analysis was taken without factoring in the complexity of designing or building a subsystem to accomplish this.
  • Endgame does not require a different subsystem entirely but instead can simply be an extension of the drive subsystem
  • We will likely need two vision subsystems working simultaneously: one for robot localization via apriltags and one for system alignment for placing game pieces
  • We can likely use a gyro to automatically stabilize on the charging station, in combination with locking our swerve drive
  • We need to build a grasper to reliably handle both objects – something to keep in mind is that you can only extend over your frame perimeter in one direction at any given time

We will be meeting again today and working on predicting alliances and deciding what we want to work on moving forward for our robot. We will also be sorting out how to make a minimal setup to practice with.

We will continue to update you all on our progress in this thread, and as always, if you have any questions please feel free to reach out!

Best wishes,
Team 1757

Written by Claire, Luke, Landon, and Sean


Five Minutes…I let the drive team play with the game pieces for 5 Minutes


If that’s how the cone looks, I wonder if the cube will survive.

in my defense…
I have none