Wiki

wiki/Competition_Prep/Duluth_Regional_Itinerary.md

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+# DULUTH COMPETITION ITINERARY
+
+## Select pit crew and drive team members will drive up with mentors on Wednesday night to set up pits and prepare for practice matches the following day.
+
+## **Thursday, March 5**: Casual uniform day (any KnightKrawler/Irondale spirit wear)
+
+9:00AM: Coach bus (Lorenz) departs Irondale High School to the hotel. Once at the hotel, students unload luggage in the hotel conference room (will pick up after practice matches and the team feed), eat a sack lunch (provided by the team) at the hotel, and walk to the DECC 
+
+12:00PM: Practice matches begin at the DECC
+
+6:15PM: Team feed at the hotel; students check in to rooms and unload luggage
+
+10:00PM: Students report back to their individual rooms for room checks; lights out is at 10:30PM
+
+## **Friday, March 6**: Formal uniform day (gold t-shirt and maroon work shirt)
+
+→ Breakfast is provided by the Hampton Inn. Students should eat before leaving the hotel.
+
+8:30AM: Opening ceremonies at the DECC
+
+9:00AM: Qualification matches begin at the DECC
+
+12:00PM: Lunch break (1 hour) \- Students get lunch (team feed or concessions)
+
+1:00PM: Qualifications matches resume at the DECC with an awards ceremony beginning at 5:45PM
+
+6:15PM: Awards ceremony concludes, and students eat dinner at the hotel in chaperoned groups
+
+10:00PM: Students report back to their individual rooms for room checks; lights out is at 10:30PM
+
+## **Saturday, March 7**: Formal uniform day (gold t-shirt and maroon work shirt)
+
+PRIOR TO 8:00am: clear rooms and bring luggage to the designated baggage claim area before leaving for the DECC  
+→ Breakfast is provided by the Hampton Inn. Students should eat before leaving the hotel.
+
+8:30AM: Opening ceremonies at the DECC
+
+9:00AM: Qualification matches begin at the DECC, with alliance selection following them
+
+12:30PM: Lunch break (1 hour) \- students get lunch (team feed or concessions)
+
+1:30PM: Playoff matches begin with an awards ceremony following the conclusion of all matches
+
+6:00PM: Students return to the hotel to get luggage and get on the bus back to Irondale High School. Students may purchase a meal on the way home (we usually have one fast food stop). We usually get to Irondale High School around 9-9:30PM. 

wiki/Competition_Prep/Week_Zero/Field_Setup_and_Safety.md

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+# Week Zero \- Field Set Up and Event Safety
+
+## Week Zero Field Configuration and Set Up
+
+Just like in a regular season competition, the Week Zero field is divided into 3 sections: 
+
+* Field  
+* Pits  
+* Audience
+
+An example event layout is shown in the configuration: [Week Zero Field Layout Example](https://team2052.com/assets/downloads/WeekZeroFieldLayout.pdf)
+
+The Friday before the Week Zero event, volunteers are needed to set up the field in the main gym of Irondale. The field setup can take 4 or five hours because it involves putting down tarps, masonite boards, and carpet; laying out the field; and erecting the field elements. We try to get an early start but often there are basketball games going until 8 or 9pm.
+
+In the afternoon after the event, volunteers help tear down the field and put it back into storage.
+
+## Week Zero Event Safety
+
+During Week Zero, a designated Safety Team will monitor the event for any reported safety concerns. The team will consist of a small group that has familiarity with the running of the event or has a special skill, such as EMT or a First Responder.
+
+Safety team members need to be familiar with the Safety Manual and the **Hold**, **Secure**, **Lockdown**, **Evacuate**, and **Shelter** procedure protocols described in the [Standard Response Protocol](https://team2052.com/http://127.0.0.1:4000/wiki/Safety/Standard_Response_Protocol/)  

wiki/General/Points.md

@@ -19,7 +19,6 @@ In this way, points are the primary metric for progress tracking across our team
 Activities corresponding to a point logged on a student point sheet must be team-related, but there are a wide variety of point types students can track across subteams and leadership / team management roles.
 
 Examples of Subteam (Programming, More Than Robots (Media), Build) points include tasks like completing a scale drawing or model of an intake, putting together clips for a reveal video, or programming and testing a new drivebase system. Students may also gain points for attending certain events, such as Jumpstart or information sessions at MRI (Firebears Minnesota Robotics Invitational) if they include a photograph of notes they took at such events.   
-
 Non-points include tasks like “put a wrench away,” “downloaded programming resources,” or other work that would not require 3-4 hours of engaged work. Attendance at meetings is also not eligible to earn a point.
 
 Additionally, KnightKrawler places emphasis on points as a representation of completion or significant progress on some task or activity. Points are not meant to represent an accumulation of smaller, unrelated or day-to-day tasks across a 3-4 hour period that are combined into one singular point. Attendance and productivity at a meeting is not necessarily a point, but a student working on a focused project across multiple meetings for a total of 3-4 hours and reaching some significant milestone in their progress is.

wiki/Outreach/Girls_In_The_Shop.md

@@ -40,8 +40,7 @@ Afterwards, students began to split into the 4 main stations. At one station, st
 
 At each major tool station (drill press and saw), we had a supervising adult. Other adults mingled through the rest of the stations, providing support where needed and allowing student leaders and new students to drive where needed. 
 
-![][image1]
-![][image2]  
+![][image1]![][image2]
 
 ## Reflection on the 2025 Girls in the Shop Event
 

wiki/Outreach/KOP_Pickup.md

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+# KOP Pickup
+
+KnightKrawler is a KOP Pickup location for teams to pick up their game specific box as well as KOP Chassis and Black Tote (if applicable) on the day of FRC Kick Off.
+
+### Staffing:  
+
+6 total
+
+### Assignments:  
+
+1 person with materials inside & keeping paperwork organized  
+2 people outside checking in team representatives picking up  
+2 people distributing materials to cars, initial greeter, check in team, hand off paperwork to second person for paperwork verification, and communicating needed materials being picked up with distributing staff  
+1 person moving/staging materials outside as needed
+
+### Supplies:
+
+Tarp  
+Table and chair inside  
+Dolly for moving items  
+2 clipboards   
+Pens   
+Computer  
+Consider using ipads (2) instead of pen/paper
+
+### Timeline:
+
+XXX \- sign up as KOP site & designate key volunteers  
+XXX \- Check school calendar for other scheduled events day of pick up that may affect logistics for pick up.  Communicate to teams via email with pick up information  
+3 weeks prior to kick off, prepare area in secure storage locker (room 19\) for KOP material storage   
+1-2 weeks prior when shipped by FIRST, receive materials and move to storage area, inventory with second person & secure with tarp
+
+### Day of kickoff: 
+
+Move materials to lobby about 30 minutes prior to release time & set up work area  
+Move initial stock of materials to outdoors (or just inside lobby if inclement weather) at release time when can start to distribute

wiki/Programming/Object_Detection.md

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+# Object Detection Steps and Resources
+
+[Limelight documentation for training a model](https://docs.limelightvision.io/docs/docs-limelight/pipeline-neural/training-your-own-detector)
+
+- Read through this for steps  
+- Look @ Roboflow Universe for models  
+- Figure out how to combine them??
+
+[Where to upload the model](https://tools.limelightvision.io/neural-network-trainer)  \- once you have all your annotated date
+
+1. What is object detection & how have we used it in the past  
+2. Find models on [RoboFlow Universe](https://universe.roboflow.com/)  
+   1. What makes a good model  
+      1. Variety of images \- different contexts  
+3. [Converting COCO JSON to Tensorflow TF Record](https://roboflow.com/convert/coco-json-to-tensorflow-tfrecord)  
+   1. Step 1: set up the project  
+   2. Step 2: upload your data to the project  
+      1. Download the models you found as .coco files  
+      2. Upload data to the model → move in the coco files & upload them to the dataset  
+   3. Step 3 dataset version  
+      1. Auto orient  
+      2. Resize  
+      3. grayscale   
+      4. ![][image1]  
+   4. Step 4  
+      1. Add 90 degree rotation  
+      2. Add \+ & \- 15 degree brightness  
+   5. Download tensorflow tf record  
+4. Now you’ve created a new version  
+5. Upload final [TF Record model](https://tools.limelightvision.io/neural-network-trainer) \<- TO THIS LINK  
+   1. Train the model (takes some time)  
+   2. When done, you get a tf.white file  
+6. Add to the code \- follow [Upload to Limelight step HERE](https://docs.limelightvision.io/docs/docs-limelight/pipeline-neural/training-your-own-detector)  
+7. 7.5 Detector Results → use API call to grab the location information  
+8. Look HERE (2024 Crescendo) for an example of a [Game Piece Alignment Command](https://github.com/frc2052/2024-Crescendo/blob/main/src/main/java/frc/robot/commands/drive/GamePieceAlignmentCommand.java)
+
+[image1]: <data:image/png;base64,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>