Jackson is a very heavy library; it supports loads of features that we
don't need, and historically has caused issues due to long class loading
times (a little over 2 seconds to load AprilTagFieldLayout). This often
manifests as a help request in the form of "my robot disables when I do
X, but doesn't disable when doing X in subsequent attempts until code
restart." While SC has brought down Jackson loading times significantly,
with AprilTagFieldLayout loads taking only 330 milliseconds, that's
still a rather long delay, and while libraries should handle any JSON
loading ahead of time to prevent delays in auto/teleop, it would still
be good to make the worst case better to reduce user frustration.
Benchmarks indicate using [Avaje
Jsonb](https://github.com/avaje/avaje-jsonb) to load AprilTagFieldLayout
only takes ~70 ms, a fair chunk of which isn't actually in Avaje Jsonb
(~4 ms is spent on using getResourceAsStream to retrieve the JSON file,
~8 ms is spent on just loading the AprilTag class and its dependencies).
Note that all times listed are end-to-end, meaning nothing else was done
except for the operation being benchmarked, and doing arithmetic on them
can be flawed due to some classes being loaded twice, i.e.,
getResourceAsStream and `new AprilTag()` likely load some of the same
JDK classes and so subtracting both from the Avaje Jsonb load time is
likely slightly incorrect because class loading is being double counted.
For our purposes, it's likely accurate enough and is mostly just for
contextualization.
Benchmarks were run on a Raspberry Pi CM5 with 2 GB of RAM. Source code
for the
[results](https://github.com/user-attachments/files/26471452/benchmark.txt)
can be found in the "Fastjson2" commit
(2456d15ca8ebd17635e607cd40bf8816e77869a1).
Avaje Jsonb uses code generation via annotation processors to generate
the classes needed to do JSON serde and uses service providers to find
them, which will require downstream changes in robot projects, as the
different service providers in each library must be merged together for
Avaje Jsonb to function. We will use the Gradle shadow plugin, as its
already used by the installer and therefore adds zero additional
dependencies.
There's changes to the diagnostic output and a performance improvement
for autodiff setup. I also updated Java's Options docs to more closely
match upstream.
The wrapper includes reverse mode autodiff, the Problem DSL, and the
optimal control problem API. I wrote it by directly translating the
upstream
[API](https://github.com/SleipnirGroup/Sleipnir/tree/main/include/sleipnir)
and [tests](https://github.com/SleipnirGroup/Sleipnir/tree/main/test) to
Java (i.e., copy-paste-modify).
I replaced the ArmFeedforward and Ellipse2d JNIs with implementations
using the Sleipnir Java bindings. Switching dev binary JNIs to release
by default sped up wpimath test runs from several minutes to 7 seconds.
- Remove status return from HAL level (clock getting should never fail)
- Remove 32-bit timestamp expand function
- Make monotonic_clock.hpp (formerly fpga_clock.hpp) header-only and
move to root hal include directory
I left "free speed" alone since that's the technical term for it. In
general, velocity is a vector quantity, and speed is a magnitude (i.e.,
a strictly positive value).
This PR also replaces the speed verbiage in MotorController with duty
cycle.
Fixes#8423.
This hooks up the bazel build to the robotpyExamples. It can use the
(formly pyfrc or whatever) automatic unit tests for an example, as well
as exposing the ability to run the example in simulation, with or
without `halsim_gui` with a command such as `bazel run
//robotpyExamples:AddressableLED-sim`
This required building and using wheels instead of just a normal
`py_library`, so that things like `ENTRY_POINTS` can be used. I took a
bare bones approach to building and naming the wheels (for example the
native ones don't have the OS info or python version in them, so they
wouldn't be suitable publish to pypi, but that can always be updated
later.
Avoids boxing to reduce allocations, combines for loops as an
optimization, and removes massive switch statement because Java's
generics are type erased, so the different type parameters make no
difference.
Also fixes the google compile-testing library to 0.23.0 (the latest
available at time of writing) instead of a wildcard
Jackson versions were inconsistent across projects; most were on 2.19.2,
but the fields subproject was on 2.15.2. All projects are now on 2.19.2
for consistency
In C++, we use a diagonal matrix to avoid an expensive matrix
multiplication. EJML doesn't have a diagonal matrix type, so in Java, we
use a double array and implement the multiplication manually.
Add a simple tap counting filter for boolean streams.
The filter activates when the input has risen (transitioned from false
to true, like when a button is tapped) the required number of times
within the time window after the first rising edge. Once activated, the
output remains true as long as the input is true. The tap count resets
when the time window expires or when the input goes false after
activation.
Example usage:
```java
xbox.a()
.multiPress(2, 0.2) // Detect a double tap within 0.2 seconds
.onTrue(Commands.print("Double tapped A button"));
xbox.y()
.multiPress(2, 0.5) // Detect a double tap within 0.5 seconds
.whileTrue(Commands.print("Y held after tap").repeatedly());
```
This is not a noise reduction and/or input smoothing filter, but it is
similar in usage to debounce, so I believe it could be considered a
filter, but am open to a better location.
I believe this would be a useful addition, as double/triple tapping a
button is a common control option in games, yet is not often utilized by
newer FRC teams. I believe adding it to WPILib in a standard way will
allow more teams to make the most out of their controls.
Documents the extrinsic vs intrinsic semantics of `plus()` and
`minus()`. (`rotateBy()` was documented in [a previous
PR](https://github.com/wpilibsuite/allwpilib/pull/5508))
Fixes usage of `plus()` and `minus()` in `Rotation3d.interpolate()`.
(Fixes#8523)
Fixes incorrect usages of `plus()`, `minus()`, and `rotateBy()`
throughout `Odometry3d`.
Adds explanatory comments for some `plus()`, `minus()`, and `rotateBy()`
operations.
Fixes `TimeInterpolatableBuffer` not using twists for `Pose3d` (this was
just because I happened to notice it, it isn't really related to the PR)
To check all of our usages of `plus()`, `minus()`, and `rotateBy()`, I
marked them as deprecated, checked compile errors from `./gradlew
compileJava`, and then undeprecated them. You can see all of the spots
that showed up (at least on the Java side) by viewing the diff for
241109c.
I wanted to present this alternative to #8526 because the change has its
own quirks, there's little time before kickoff, and there would be no
code-side warning to teams (and mentors) already used to the current
behavior.
Used Gemini to convert the C++ tests in wpimath/.../kinematics to
pytest. For ease of use required a better constructor for
`MecanumDriveWheelPositions`
I did this conversion months ago (before robotpy landed and before the
reorg), so new tests might be missing. At least its better than nothing
🤷
Broke the huge pr that does almost everything into parts so its easier
to review.
---------
Co-authored-by: David Vo <auscompgeek@users.noreply.github.com>
Resync with `mostrobotpy`
This mostly involves the big "ignore almost everything in the HAL
project" and some fixups for the Addressable LED classes.
Required two small hand fixes to get it building over here with bazel,
and with more compiler warnings on.
I also manually zeroed out the `repo_url` field in the toml files to
avoid unnecessary churn whenever it goes from a release build to a
development build. I already did this with `version` field in there, and
will do a follow up PR that updates the copybara script to do it
automatically.
---------
Co-authored-by: Default email <default@default.com>
I tried to sync `mostrobotpy` with `allwpilib` and was getting a
compilation error I had not seen before when it tried to do the stub
generation (which `allwpilib` does not do).
Luckily, I was able to debug it here by writing some unit tests (i.e.,
having Gemini convert the C++ tests into python) that failed in a
similar way. The main problem was needing to write a custom constructor
for the class and adding a `force_type_casters`. I used `ChassisSpeed`
as my main example, but I did not copy all of the other custom code like
overriding the index operator, `__repr__` operator, feet helpers, etc. I
can gladly add those in.
In the future, we should start enforce a policy that if you add a C++ or
Java unit test, you also have to add a python test. That developer might
have gotten more stuck on the minutia of how to fix it, but this problem
would have at least been caught earlier before it landed.
This got missed in the reorg, and these values aren't actually used for
anything when building in `allwpilb`, but we might as well fix them here
to make the copybara process easier.
Fixes https://github.com/wpilibsuite/allwpilib/issues/8284.
If we have vision updates at the time of the `Reset*` call, we can
correct the translation/rotation of the new odometry pose by adding a
new vision update where:
- `ResetTranslation`: the translation is hard-coded to the new
translation, and the rotation components are set to those of the latest
vision update (prior to clearing the map).
- `ResetRotation`: the rotation is hard-coded to the new rotation, and
the translation components are set to those of the latest vision update
(prior to clearing the map).
ChassisAccelerations and the drivetrain acceleration types are added in
both Java and C++. `ChassisAccelerations` is basically just
`ChassisSpeeds` but for accelerations!
`DifferentialDriveWheelAccelerations`, `MecanumDriveWheelAccelerations`,
and `SwerveModuleAccelerations` are the acceleration equivalent of the
drivetrain speeds types.
In Java, the `Kinematics` interface now has an additional generic
parameter `A` which represents the accelerations, and
`toChassisAccelerations` and `toWheelAccelerations` methods, which are
implemented the same way as `toChassisSpeeds` and `toWheelSpeeds`.
Protobuf and struct classes were also added for all four classes in Java
and C++.
---------
Signed-off-by: Zach Harel <zach@zharel.me>
Co-authored-by: Joseph Eng <91924258+KangarooKoala@users.noreply.github.com>
Co-authored-by: Tyler Veness <calcmogul@gmail.com>
* Moved makeWhiteNoiseVector() to random.Normal.normal()
* Moved isControllable() and isDetectable() to system.LinearSystemUtil
* Renamed makeCostMatrix() to costMatrix() (Java)
* Renamed makeCovarianceMatrix() to covarianceMatrix() (Java)
* Renamed MakeCostMatrix() to CostMatrix() (C++)
* Renamed MakeCovMatrix() to CovarianceMatrix() (C++)
* Removed deprecated poseTo3dVector(), poseTo4dVector(), poseToVector()
* Removed clampInputMaxMagnitude()
* We don't use it, and Eigen has this functionality built in via `u =
u.array().min(u_max.array()).max(u_min.array());`
* Simplified implementation of desaturateInputVector()
