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Documentation Updates #126

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d35f50e
Add GSG instructions related to building the Pi Box
tbowers7 Jan 27, 2026
6877bf9
Limit stall current
tbowers7 Jan 28, 2026
aa69226
Merge branch 'main' into doc_updates
tbowers7 Jan 31, 2026
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Merge branch 'develop' into doc_updates
tbowers7 Feb 3, 2026
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Merge branch 'develop' into doc_updates
tbowers7 Feb 5, 2026
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Begin the vision documentation
tbowers7 Feb 7, 2026
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5 changes: 4 additions & 1 deletion doc/INSTALL.md
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Expand Up @@ -118,7 +118,10 @@ steps you need to complete:
https://github.com/CrossTheRoadElec/Phoenix6-Examples/blob/1db713d75b08a4315c9273cebf5b5e6a130ed3f7/java/SwerveWithPathPlanner/src/main/java/frc/robot/generated/TunerConstants.java#L171-L175).
Before removing them, both lines will be marked as errors in VSCode.

5. In `TunerConstants.java`, change `kSteerInertia` to `0.004` and
5. In `TunerConstants.java`, change `kSlipCurrent` to `60` amps. This will
keep your robot from tearing holes in the carpet at competition!

6. In `TunerConstants.java`, change `kSteerInertia` to `0.004` and
`kDriveInertia` to `0.025` to allow the AdvantageKit simulation code to
operate as expected.

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19 changes: 19 additions & 0 deletions doc/RBSI-GSG.md
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Expand Up @@ -41,6 +41,10 @@ modifications to extant RBSI code will be done to files within the

### Tuning constants for optimal performance

**It cannot be overemphasized the importance of tuning your drivetrain for
smooth and consistent performance, battery longevity, and not tearing up the
field.**

4. Over the course of your robot project, you will need to tune PID parameters
for both your drivebase and any mechanisms you build to play the game.
AdvantageKit includes detailed instructions for how to tune the various
Expand Down Expand Up @@ -132,3 +136,18 @@ section of [each release](https://github.com/AZ-First/Az-RBSI/releases).

Mounting the case to the robot requires 4x #10-32 nylock nuts (placed in the
hex-shaped mounts inside the case) and 4x #10-32 bolts.

Order of addembly of the Orange Pi Double Case matters given tight clearances:
1. Super-glue the nylock nuts into the hex mounting holes.
2. Intall the fans and grates into the case side.
3. Assemble the Pi's into the standoffs outside the box.
4. Solder / mount the Voltage Regular solution of your choice.
5. Connect the USB-C power cables to the Pi's.
6. Connect the fan power to the 5V (red) and GND (black) pins in the Pi's.
7. Install the Pi/standoff assembly into the case using screws at the bottom,
be careful of the tight clearance between the USB sockets and the case opening.
8. Tie a knot in the incoing power line _to be placed inside the box
for strain relief_, and pass the incoming power line through the notch
in the lower case.
9. Install the cover on the box using screws.
10. Mount the case to your robot using the #10-32 screws.
72 changes: 72 additions & 0 deletions doc/RBSI-Vision.md
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# Az-RBSI Vision Integration

This page includes detailed steps for integrating robot vision for your
2026 REBUILT robot.

--------

### PhotonVision

The preferred method for adding vision to your robot is with [PhotonVision](
https://photonvision.org/). This community-developed open-source package
combines coprocessor-based camera control and analysis with a Java library
for consuming the processed targeting information in the robot code.

#### Recommended Setup with Az-RBSI

We recommend using Arducam [OV9281](https://www.amazon.com/dp/B096M5DKY6)
(black & white) and/or [OV9782](https://www.amazon.com/dp/B0CLXZ29F9) (color)
cameras for robot vision due to their Global Shutter, Low Distortion, and USB
connection. In addition to the lens delivered with the camera, supplementary
lenses may be purchased to vary the FOV available to the detector for various
robot applications, such as [Low-Distortion](
https://www.amazon.com/dp/B07NW8VR71) or [General Purpose](
https://www.amazon.com/dp/B096V2NP2T).

For the coprocessor that controls the cameras and analyzes the images for
AprilTag and gamepiece detection, we recommend using one or two Orange Pi 5
single-board computers -- although PhotonVision does support a number of
[different coprocessor options](
https://docs.photonvision.org/en/latest/docs/quick-start/quick-install.html).
As decribed in the [Getting Started Guide](RBSI-GSG.md), we include a 3D print
for a case that can hold one or two of these computers.

#### Setting up PhotonVision on the Coprocessor

Download the appropriate [disk image](
https://github.com/PhotonVision/photonvision/releases/tag/v2026.2.1) for your
coprocessor and burn it to an SD card using the [Raspberry Pi Imager](
https://www.raspberrypi.com/software). Connect the powered-on coprocessor
to a network switch via ethernet, and connect to the PhotonVision software
at the address ``http://photonvision.local:5800``.

Before you connect the coprocessor to your robot, be sure to set your team
number, set the IP address to "Static" and give it the number ``10.TE.AM.11``,
where "TE.AM" is the approprate parsing of your team number into IP address,
as used by your robot radio and RoboRIO. If desired, you can also give your
coprocessor a hostname.

![PhotonVision Network Settings](PV_Network.png)

We suggest you give your first coprocessor the static IP address
``10.TE.AM.11``, and your second coprocessor (if desired) ``10.TE.AM.12``.
The static address allows for more stable operation, and the these particular
addresses do not conflict with other devices on your robot network.

Plug in cameras (two or three per coprocessor) and navigate to the Camera
Configs page (see below). Activate the cameras.

![PhotonVision Camera Configs](PV_Cameras.png)

#### Configuring and Calibrating your Cameras

This is the most important part, and the description of which is left as an
exercise for the user.

Good luck!

#### Using PhotonVision for vision simulation

This is an advanced topic, and is therefore in the Restricted Section.

![Restricted Section](restricted_section.jpg)
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