Chalkydri is a blazingly fast vision system for FRC written in Rust.

In development

Chalkydri isn't ready to use quite yet.

New here?

Check out our Getting Started guide!

About

Chalkydri was created by and is managed by FRC Team 4533 (Phoenix).

We're trying to make vision less of a black box, so all FRC teams can use it, no matter their size. We also want it to be easier to use effectively with less hassle.

Chalkydri has been built from the ground up for performance on popular FRC vision hardware and uses less CPU and memory than existing solutions.

Credits

PhotonVision
- Main inspiration for the design of Chalkydri
Lincoln (Student, 4533)
- Phoenix vision code lead
Chloe (Student, 4533)
- Implemented pose estimation
Eda (Student, 4533)
- Implemented AprilTags edge checking algorithm
Drake (Student, 4533)
- Past vision code lead

This is a generic guide. You probably want a guide specific to whatever device you're using:

(Recommended) Raspberry Pi 3/4/5

If your device isn't listed here, it may work, but there's no guarantee. You can see our instructions for building from source if we aren't providing binaries for your target architecture.

Before we start, click here to start downloading our latest release. It might take a little while on poor connections.

Flashing your microSD card

We recommend Etcher, since it's easy to use and cross-platform.

It will figure everything out for you and flash Chalkydri.

That's it! Now you can learn how to use Chalkydri.

Chalkydri system design

Chalkydri has a somewhat complicated design, as most vision things do.

Once the robot is powered on, each Chalkydri device will:

Boot up
Attempt to connect to the roboRIO's NetworkTables server
Initialize camera(s)
Start subsystems

Chalkydri waits until it connects to the NetworkTables server successfully to actually start running. It will negotiate with the roboRIO and start processing frames.

NetworkTables API

Chalkydri/
    Robot/
        Position/
            X
            Y
        Rotation
    Devices/
        1/
        2/
        3/
        ...

Chalkydri/Robot/

Topics relevant to the robot as a whole

Chalkydri/Robot/Position/X (64-bit float) The robot's current X coord on the field
Chalkydri/Robot/Position/Y (64-bit float) The robot's current Y coord on the field
Chalkydri/Robot/Rotation (64-bit float) The robot's current rotation

Chalkydri/Devices/

Each device's device-specific topics are grouped under Chalkydri/Devices/{device id}/

Chalkydri/Devices/X/Version (string) The device's Chalkydri version

Maintenance guide

This is for people working on Chalkydri itself

If you are a Chalkydri user, this isn't what you want.

Being a fairly advanced project as FRC goes, it's harder to just pick up and work on.

This is the incomplete guide to maintaining it, how the internals work, and the best learning resources.

The Chalkydri project has several subprojects, mostly libraries we needed to build it.

MiniNT

Our NetworkTables client implementation

The existing Rust implementation was overly complex and pulled in too many extra dependencies. We tried a fork, but ended up just implementing NT4 from scratch.

TFLedge

Our bindings to TensorFlow Lite and libedgetpu

Here's all the awesome learning resources I've found so far:

Getting started

(Linux) Command Line for Beginners
(Linux) The Linux Command Handbook
(Rust) The Book
(Rust) Rust by Example (interactive, web)
(Rust) Rustlings (interactive, native)

Getting deeper

The Rustonomicon (unsafe Rust code)

Chalkydri is built on and for Linux, so using other operating systems may be a little more difficult.

Dev containers

Dev containers streamlines the development process by sharing a preconfigured environment that has everything we need inside of a container. If you're using VS Code, you can follow Microsoft's guide here to get everything set up on Linux, Windows, or Mac.

Manually

WIP

Raspberry Pi

The Pi 3, 4, and 5 are supported.

Pi cameras

libcamera is required to interact with v3.

Coral Edge TPU

We made our own bindings to TFLite and libedgetpu.

Releases should be done with CI.

To release a new version, simply create a release on Github. CI will test and build the main branch.

AprilTags

We're using our own custom AprilTag library, chalkydri-apriltags, built from the ground up. We'll refer to it as "CAT".

API documentation (rustdoc)

Why?

We have a few reasons for writing our own, rather than using what's already out there. The reference C library:

is very resource intensive
uses a lot of advanced math which isn't covered in high school classes, making it harder for students to understand how it works
has memory leaks (needs a citation)