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[wpimath] Add Sleipnir Java bindings (#8236)

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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.
This commit is contained in:
Tyler Veness
2026-03-29 22:34:21 -07:00
committed by GitHub
parent 3e821b9448
commit d248c040bf
84 changed files with 13405 additions and 170 deletions
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49
wpimath/src/test/native/cpp/optimization/CurrentManagerTest.cpp Normal file
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// Copyright (c) FIRST and other WPILib contributors.
// Open Source Software; you can modify and/or share it under the terms of
// the WPILib BSD license file in the root directory of this project.
#include "wpi/math/optimization/CurrentManager.hpp"
#include <array>
#include <gtest/gtest.h>
TEST(CurrentManagerTest, EnoughCurrent) {
wpi::math::CurrentManager manager{std::array{1.0, 5.0, 10.0, 5.0}, 40.0};
auto currents = manager.calculate(std::array{25.0, 10.0, 5.0, 0.0});
EXPECT_NEAR(currents[0], 25.0, 1e-3);
EXPECT_NEAR(currents[1], 10.0, 1e-3);
EXPECT_NEAR(currents[2], 5.0, 1e-3);
EXPECT_NEAR(currents[3], 0.0, 1e-3);
}
TEST(CurrentManagerTest, NotEnoughCurrent) {
wpi::math::CurrentManager manager{std::array{1.0, 5.0, 10.0, 5.0}, 40.0};
auto currents = manager.calculate(std::array{30.0, 10.0, 5.0, 0.0});
// Expected values are from the following program:
//
// #!/usr/bin/env python3
//
// from scipy.optimize import minimize
//
// r = [30.0, 10.0, 5.0, 0.0]
// q = [1.0, 5.0, 10.0, 5.0]
//
// result = minimize(
// lambda x: sum((r[i] - x[i]) ** 2 / q[i] ** 2 for i in range(4)),
// [0.0, 0.0, 0.0, 0.0],
// constraints=[
// {"type": "ineq", "fun": lambda x: x},
// {"type": "ineq", "fun": lambda x: 40.0 - sum(x)},
// ],
// )
// print(result.x)
EXPECT_NEAR(currents[0], 29.960, 1e-3);
EXPECT_NEAR(currents[1], 9.008, 1e-3);
EXPECT_NEAR(currents[2], 1.032, 1e-3);
EXPECT_NEAR(currents[3], 0.0, 1e-3);
}