The Field2d Widget

Glass supports displaying your robot’s position on the field using the Field2d widget. An instance of the Field2d class should be created, sent over NetworkTables, and updated periodically with the latest robot pose in your robot code.

Sending Robot Pose from User Code

To send your robot’s position (usually obtained by odometry or a pose estimator), a Field2d instance must be created in robot code and sent over NetworkTables. The instance must then be updated periodically with the latest robot pose.

JAVA

private final Field2d m_field = new Field2d();

// Do this in either robot or subsystem init
SmartDashboard.putData("Field", m_field);

// Do this in either robot periodic or subsystem periodic
m_field.setRobotPose(m_odometry.getPoseMeters());

C++

#include <frc/smartdashboard/Field2d.h>
#include <frc/smartdashboard/SmartDashboard.h>

frc::Field2d m_field;

// Do this in either robot or subsystem init
frc::SmartDashboard::PutData("Field", &m_field);

// Do this in either robot periodic or subsystem periodic
m_field.SetRobotPose(m_odometry.GetPose());

PYTHON

from wpilib import SmartDashboard, Field2d

self.field = Field2d()

# Do this in either robot or subsystem init
SmartDashboard.putData("Field", self.field)

# Do this in either robot periodic or subsystem periodic
self.field.setRobotPose(self.odometry.getPose())

Note

The Field2d instance can also be sent using a lower-level NetworkTables API or using the Shuffleboard API. In this case, the SmartDashboard API was used, meaning that the Field2d widget will appear under the SmartDashboard table name.

Sending Trajectories to Field2d

Visualizing your trajectory is a great debugging step for verifying that your trajectories are created as intended. Trajectories can be easily visualized in Field2d using the setTrajectory()/SetTrajectory() functions.

JAVA

  public void robotInit() {
    // Create the trajectory to follow in autonomous. It is best to initialize
    // trajectories here to avoid wasting time in autonomous.
    m_trajectory =
        TrajectoryGenerator.generateTrajectory(
            new Pose2d(0, 0, Rotation2d.fromDegrees(0)),
            List.of(new Translation2d(1, 1), new Translation2d(2, -1)),
            new Pose2d(3, 0, Rotation2d.fromDegrees(0)),
            new TrajectoryConfig(Units.feetToMeters(3.0), Units.feetToMeters(3.0)));

    // Create and push Field2d to SmartDashboard.
    m_field = new Field2d();
    SmartDashboard.putData(m_field);

    // Push the trajectory to Field2d.
    m_field.getObject("traj").setTrajectory(m_trajectory);
  }

C++

  void AutonomousInit() override {
    // Start the timer.
    m_timer.Start();

    // Send Field2d to SmartDashboard.
    frc::SmartDashboard::PutData(&m_field);

    // Reset the drivetrain's odometry to the starting pose of the trajectory.
    m_drive.ResetOdometry(m_trajectory.InitialPose());

    // Send our generated trajectory to Field2d.
    m_field.GetObject("traj")->SetTrajectory(m_trajectory);
  }

PYTHON

    def robotInit(self):

        # An example trajectory to follow during the autonomous period.
        self.trajectory = wpimath.trajectory.TrajectoryGenerator.generateTrajectory(
            wpimath.geometry.Pose2d(0, 0, wpimath.geometry.Rotation2d.fromDegrees(0)),
            [
                wpimath.geometry.Translation2d(1, 1),
                wpimath.geometry.Translation2d(2, -1),
            ],
            wpimath.geometry.Pose2d(3, 0, wpimath.geometry.Rotation2d.fromDegrees(0)),
            wpimath.trajectory.TrajectoryConfig(
                wpimath.units.feetToMeters(3.0), wpimath.units.feetToMeters(3.0)
            ),
        )

        # Create Field2d for robot and trajectory visualizations.
        self.field = wpilib.Field2d()

        # Create and push Field2d to SmartDashboard.
        wpilib.SmartDashboard.putData(self.field)

        # Push the trajectory to Field2d.
        self.field.getObject("traj").setTrajectory(self.trajectory)

Viewing Trajectories with Glass

The sent trajectory can be viewed with Glass through the dropdown NetworkTables -> SmartDashboard -> Field2d.

Note

The above example which uses the RamseteController (Java / C++ / Python) will not show the sent trajectory until autonomous is enabled at least once.

Viewing the Robot Pose in Glass

After sending the Field2d instance over NetworkTables, the Field2d widget can be added to Glass by selecting NetworkTables in the menu bar, choosing the table name that the instance was sent over, and then clicking on the Field button.

Once the widget appears, you can resize and place it on the Glass workspace as you desire. Right-clicking the top of the widget will allow you to customize the name of the widget, select a custom field image, select a custom robot image, and choose the dimensions of the field and robot.

You can choose from an existing field layout using the Image drop-down. Or you can select a custom file by setting the Image to Custom and selecting Choose image…. You can choose to either select an image file or a PathWeaver JSON file as long as the image file is in the same directory. Choosing the JSON file will automatically import the correct location of the field in the image and the correct size of the field.

Note

You can retrieve the latest field image and JSON files from here. This is the same image and JSON that are used when generating paths using PathWeaver.

Modifying Pose Style

Poses can be customized in a plethora of ways by right clicking on the Field2d menu bar. Examples of customization are: line width, line weight, style, arrow width, arrow weight, color, etc.

One usage of customizing the pose style is converting the previously shown traj pose object to a line, rather than a list of poses. Click on the Style dropdown box and select Line. You should notice an immediate change in how the trajectory looks.

Now, uncheck the Arrows checkbox. This will cause our trajectory to look like a nice and fluid line!

Viewing Pose Data with AdvantageScope

AdvantageScope is an alternative option for viewing pose data from a Field2d object, including data recorded to a log file using WPILib data logs. Both 2D and 3D visualizations are supported. See the documentation for the odometry and 3D field tabs for more details.