[examples] Add Computer Vision Pose Estimation and Latency Compensation Example (#4901)

This PR updates the existing differentialdriveposeestimator example to include computer vision pose estimation and latency compensation.

The example generates a simulated cameraToTarget transformation, which is then fed into ComputerVisionUtil.objectToRobotPose() to compute the robot's field-relative position exclusively from vision measurements. The vision measurements are applied through DifferentialDrivePoseEstimator.addVisionMeasurement().

The updated example constructs an AprilTagFieldLayout from JSON. This requires a deploy directory, something which isn't currently supported in wpilibjExamples and wpilibcExamples.
This commit is contained in:
CarloWoolsey
2023-01-18 20:46:05 -08:00
committed by GitHub
parent cb9b8938af
commit 371d15dec3
5 changed files with 386 additions and 35 deletions

View File

@@ -4,10 +4,31 @@
#include "Drivetrain.h"
#include <frc/Timer.h>
#include "ExampleGlobalMeasurementSensor.h"
Drivetrain::Drivetrain() {
// We need to invert one side of the drivetrain so that positive voltages
// result in both sides moving forward. Depending on how your robot's
// gearbox is constructed, you might have to invert the left side instead.
m_rightGroup.SetInverted(true);
m_gyro.Reset();
// Set the distance per pulse for the drive encoders. We can simply use the
// distance traveled for one rotation of the wheel divided by the encoder
// resolution.
m_leftEncoder.SetDistancePerPulse(
(2 * std::numbers::pi * kWheelRadius / kEncoderResolution).value());
m_rightEncoder.SetDistancePerPulse(
(2 * std::numbers::pi * kWheelRadius / kEncoderResolution).value());
m_leftEncoder.Reset();
m_rightEncoder.Reset();
frc::SmartDashboard::PutData("FieldSim", &m_fieldSim);
frc::SmartDashboard::PutData("Approximation", &m_fieldApproximation);
}
void Drivetrain::SetSpeeds(const frc::DifferentialDriveWheelSpeeds& speeds) {
const auto leftFeedforward = m_feedforward.Calculate(speeds.left);
const auto rightFeedforward = m_feedforward.Calculate(speeds.right);
@@ -25,16 +46,86 @@ void Drivetrain::Drive(units::meters_per_second_t xSpeed,
SetSpeeds(m_kinematics.ToWheelSpeeds({xSpeed, 0_mps, rot}));
}
void Drivetrain::PublishCameraToObject(
frc::Pose3d objectInField, frc::Transform3d robotToCamera,
nt::DoubleArrayEntry& cameraToObjectEntry,
frc::sim::DifferentialDrivetrainSim drivetrainSimulator) {
frc::Pose3d robotInField{drivetrainSimulator.GetPose()};
frc::Pose3d cameraInField = robotInField + robotToCamera;
frc::Transform3d cameraToObject{cameraInField, objectInField};
// Publishes double array with Translation3D elements {x, y, z} and Rotation3D
// elements {w, x, y, z} which describe the cameraToObject transformation.
std::array<double, 7> val{cameraToObject.X().value(),
cameraToObject.Y().value(),
cameraToObject.Z().value(),
cameraToObject.Rotation().GetQuaternion().W(),
cameraToObject.Rotation().GetQuaternion().X(),
cameraToObject.Rotation().GetQuaternion().Y(),
cameraToObject.Rotation().GetQuaternion().Z()};
cameraToObjectEntry.Set(val);
}
frc::Pose3d Drivetrain::ObjectToRobotPose(
frc::Pose3d objectInField, frc::Transform3d robotToCamera,
nt::DoubleArrayEntry& cameraToObjectEntry) {
std::vector<double> val{cameraToObjectEntry.Get()};
// Reconstruct cameraToObject Transform3D from networktables.
frc::Translation3d translation{units::meter_t{val[0]}, units::meter_t{val[1]},
units::meter_t{val[2]}};
frc::Rotation3d rotation{frc::Quaternion{val[3], val[4], val[5], val[6]}};
frc::Transform3d cameraToObject{translation, rotation};
return frc::ObjectToRobotPose(objectInField, cameraToObject, robotToCamera);
}
void Drivetrain::UpdateOdometry() {
m_poseEstimator.Update(m_gyro.GetRotation2d(),
units::meter_t{m_leftEncoder.GetDistance()},
units::meter_t{m_rightEncoder.GetDistance()});
// Also apply vision measurements. We use 0.3 seconds in the past as an
// example -- on a real robot, this must be calculated based either on latency
// or timestamps.
m_poseEstimator.AddVisionMeasurement(
ExampleGlobalMeasurementSensor::GetEstimatedGlobalPose(
m_poseEstimator.GetEstimatedPosition()),
frc::Timer::GetFPGATimestamp() - 0.3_s);
// Publish cameraToObject transformation to networktables --this would
// normally be handled by the computer vision solution.
PublishCameraToObject(m_objectInField, m_robotToCamera,
m_cameraToObjectEntryRef, m_drivetrainSimulator);
// Compute the robot's field-relative position exclusively from vision
// measurements.
frc::Pose3d visionMeasurement3d = ObjectToRobotPose(
m_objectInField, m_robotToCamera, m_cameraToObjectEntryRef);
// Convert robot's pose from Pose3d to Pose2d needed to apply vision
// measurements.
frc::Pose2d visionMeasurement2d = visionMeasurement3d.ToPose2d();
// Apply vision measurements. For simulation purposes only, we don't input a
// latency delay -- on a real robot, this must be calculated based either on
// known latency or timestamps.
m_poseEstimator.AddVisionMeasurement(visionMeasurement2d,
frc::Timer::GetFPGATimestamp());
}
void Drivetrain::SimulationPeriodic() {
// To update our simulation, we set motor voltage inputs, update the
// simulation, and write the simulated positions and velocities to our
// simulated encoder and gyro.
m_drivetrainSimulator.SetInputs(units::volt_t{m_leftGroup.Get()} *
frc::RobotController::GetInputVoltage(),
units::volt_t{m_rightGroup.Get()} *
frc::RobotController::GetInputVoltage());
m_drivetrainSimulator.Update(20_ms);
m_leftEncoderSim.SetDistance(m_drivetrainSimulator.GetLeftPosition().value());
m_leftEncoderSim.SetRate(m_drivetrainSimulator.GetLeftVelocity().value());
m_rightEncoderSim.SetDistance(
m_drivetrainSimulator.GetRightPosition().value());
m_rightEncoderSim.SetRate(m_drivetrainSimulator.GetRightVelocity().value());
m_gyroSim.SetAngle(-m_drivetrainSimulator.GetHeading().Degrees().value());
}
void Drivetrain::Periodic() {
UpdateOdometry();
m_fieldSim.SetRobotPose(m_drivetrainSimulator.GetPose());
m_fieldApproximation.SetRobotPose(m_poseEstimator.GetEstimatedPosition());
}

View File

@@ -15,6 +15,8 @@ class Robot : public frc::TimedRobot {
m_drive.UpdateOdometry();
}
void RobotPeriodic() override { m_drive.Periodic(); }
void TeleopPeriodic() override {
// Get the x speed. We are inverting this because Xbox controllers return
// negative values when we push forward.
@@ -31,6 +33,8 @@ class Robot : public frc::TimedRobot {
m_drive.Drive(xSpeed, rot);
}
void SimulationPeriodic() override { m_drive.SimulationPeriodic(); }
private:
frc::XboxController m_controller{0};

View File

@@ -7,13 +7,30 @@
#include <numbers>
#include <frc/AnalogGyro.h>
#include <frc/ComputerVisionUtil.h>
#include <frc/Encoder.h>
#include <frc/RobotController.h>
#include <frc/Timer.h>
#include <frc/apriltag/AprilTagFieldLayout.h>
#include <frc/apriltag/AprilTagFields.h>
#include <frc/controller/PIDController.h>
#include <frc/controller/SimpleMotorFeedforward.h>
#include <frc/estimator/DifferentialDrivePoseEstimator.h>
#include <frc/geometry/Pose2d.h>
#include <frc/geometry/Pose3d.h>
#include <frc/geometry/Quaternion.h>
#include <frc/geometry/Transform3d.h>
#include <frc/kinematics/DifferentialDriveKinematics.h>
#include <frc/motorcontrol/MotorControllerGroup.h>
#include <frc/motorcontrol/PWMSparkMax.h>
#include <frc/simulation/AnalogGyroSim.h>
#include <frc/simulation/DifferentialDrivetrainSim.h>
#include <frc/simulation/EncoderSim.h>
#include <frc/smartdashboard/Field2d.h>
#include <frc/smartdashboard/SmartDashboard.h>
#include <frc/system/plant/LinearSystemId.h>
#include <networktables/DoubleArrayTopic.h>
#include <networktables/NetworkTableInstance.h>
#include <units/angle.h>
#include <units/angular_velocity.h>
#include <units/length.h>
@@ -24,40 +41,100 @@
*/
class Drivetrain {
public:
Drivetrain() {
// We need to invert one side of the drivetrain so that positive voltages
// result in both sides moving forward. Depending on how your robot's
// gearbox is constructed, you might have to invert the left side instead.
m_rightGroup.SetInverted(true);
m_gyro.Reset();
// Set the distance per pulse for the drive encoders. We can simply use the
// distance traveled for one rotation of the wheel divided by the encoder
// resolution.
m_leftEncoder.SetDistancePerPulse(
2 * std::numbers::pi * kWheelRadius.value() / kEncoderResolution);
m_rightEncoder.SetDistancePerPulse(
2 * std::numbers::pi * kWheelRadius.value() / kEncoderResolution);
m_leftEncoder.Reset();
m_rightEncoder.Reset();
}
Drivetrain();
static constexpr units::meters_per_second_t kMaxSpeed =
3.0_mps; // 3 meters per second
static constexpr units::radians_per_second_t kMaxAngularSpeed{
std::numbers::pi}; // 1/2 rotation per second
/**
* Sets the desired wheel speeds.
*
* @param speeds The desired wheel speeds.
*/
void SetSpeeds(const frc::DifferentialDriveWheelSpeeds& speeds);
/** Drives the robot with the given linear velocity and angular velocity.
*
* @param xSpeed Linear velocity.
* @param rot Angular Velocity.
*/
void Drive(units::meters_per_second_t xSpeed,
units::radians_per_second_t rot);
/**
* Updates the field-relative position.
*/
void UpdateOdometry();
/**
* This function is called periodically during simulation. */
void SimulationPeriodic();
/** This function is called periodically, regardless of mode. */
void Periodic();
/**
* Computes and publishes to a networktables topic the transformation from
* the camera's pose to the object's pose. This function exists solely for the
* purposes of simulation, and this would normally be handled by computer
* vision.
*
* <p>The object could be a target or a fiducial marker.
*
* @param objectInField The object's field-relative position.
* @param robotToCamera The transformation from the robot's pose to the
* camera's pose.
* @param cameraToObjectEntry The networktables entry publishing and querying
* example computer vision measurements.
* @param drivetrainSimulation A DifferentialDrivetrainSim modeling the
* robot's drivetrain.
*/
void PublishCameraToObject(
frc::Pose3d objectInField, frc::Transform3d robotToCamera,
nt::DoubleArrayEntry& cameraToObjectEntry,
frc::sim::DifferentialDrivetrainSim drivetrainSimulator);
/**
* Queries the camera-to-object transformation from networktables to compute
* the robot's field-relative pose from vision measurements.
*
* <p>The object could be a target or a fiducial marker.
*
* @param objectInField The object's field-relative position.
* @param robotToCamera The transformation from the robot's pose to the
* camera's pose.
* @param cameraToObjectEntry The networktables entry publishing and querying
* example computer vision measurements.
*/
frc::Pose3d ObjectToRobotPose(frc::Pose3d objectInField,
frc::Transform3d robotToCamera,
nt::DoubleArrayEntry& cameraToObjectEntry);
private:
static constexpr units::meter_t kTrackWidth = 0.381_m * 2;
static constexpr units::meter_t kWheelRadius = 0.0508_m;
static constexpr int kEncoderResolution = 4096;
static constexpr std::array<double, 7> kDefaultVal{0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0};
frc::Transform3d m_robotToCamera{
frc::Translation3d{1_m, 1_m, 1_m},
frc::Rotation3d{0_rad, 0_rad, units::radian_t{std::numbers::pi / 2}}};
nt::NetworkTableInstance m_inst{nt::NetworkTableInstance::GetDefault()};
nt::DoubleArrayTopic m_cameraToObjectTopic{
m_inst.GetDoubleArrayTopic("m_cameraToObjectTopic")};
nt::DoubleArrayEntry m_cameraToObjectEntry =
m_cameraToObjectTopic.GetEntry(kDefaultVal);
nt::DoubleArrayEntry& m_cameraToObjectEntryRef = m_cameraToObjectEntry;
frc::AprilTagFieldLayout m_aprilTagFieldLayout{
frc::LoadAprilTagLayoutField(frc::AprilTagField::k2022RapidReact)};
frc::Pose3d m_objectInField{m_aprilTagFieldLayout.GetTagPose(0).value()};
frc::PWMSparkMax m_leftLeader{1};
frc::PWMSparkMax m_leftFollower{2};
frc::PWMSparkMax m_rightLeader{3};
@@ -90,4 +167,16 @@ class Drivetrain {
// Gains are for example purposes only - must be determined for your own
// robot!
frc::SimpleMotorFeedforward<units::meters> m_feedforward{1_V, 3_V / 1_mps};
// Simulation classes
frc::sim::AnalogGyroSim m_gyroSim{m_gyro};
frc::sim::EncoderSim m_leftEncoderSim{m_leftEncoder};
frc::sim::EncoderSim m_rightEncoderSim{m_rightEncoder};
frc::Field2d m_fieldSim;
frc::Field2d m_fieldApproximation;
frc::LinearSystem<2, 2, 2> m_drivetrainSystem =
frc::LinearSystemId::IdentifyDrivetrainSystem(
1.98_V / 1_mps, 0.2_V / 1_mps_sq, 1.5_V / 1_mps, 0.3_V / 1_mps_sq);
frc::sim::DifferentialDrivetrainSim m_drivetrainSimulator{
m_drivetrainSystem, kTrackWidth, frc::DCMotor::CIM(2), 8, 2_in};
};