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261 lines
10 KiB
Python
261 lines
10 KiB
Python
#
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# Copyright (c) FIRST and other WPILib contributors.
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# Open Source Software; you can modify and/or share it under the terms of
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# the WPILib BSD license file in the root directory of this project.
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#
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import math
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import ntcore
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import wpilib
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import wpilib.simulation
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import wpimath
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import wpimath.units
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import robotpy_apriltag
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class Drivetrain:
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"""Represents a differential drive style drivetrain."""
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kMaxSpeed = 3.0 # meters per second
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kMaxAngularSpeed = math.tau # one rotation per second
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kTrackwidth = 0.381 * 2 # meters
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kWheelRadius = 0.0508 # meters
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kEncoderResolution = 4096
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def __init__(self, cameraToObjectTopic: ntcore.DoubleArrayTopic) -> None:
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self.leftLeader = wpilib.PWMSparkMax(1)
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self.leftFollower = wpilib.PWMSparkMax(2)
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self.rightLeader = wpilib.PWMSparkMax(3)
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self.rightFollower = wpilib.PWMSparkMax(4)
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self.leftEncoder = wpilib.Encoder(0, 1)
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self.rightEncoder = wpilib.Encoder(2, 3)
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self.imu = wpilib.OnboardIMU(wpilib.OnboardIMU.MountOrientation.kFlat)
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self.leftPIDController = wpimath.PIDController(1, 0, 0)
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self.rightPIDController = wpimath.PIDController(1, 0, 0)
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self.kinematics = wpimath.DifferentialDriveKinematics(self.kTrackwidth)
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self.robotToCamera = wpimath.Transform3d(
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wpimath.Translation3d(1, 1, 1),
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wpimath.Rotation3d(0, 0, math.pi / 2),
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)
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self.defaultVal = [0.0] * 7
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self.cameraToObjectEntry = cameraToObjectTopic.getEntry(self.defaultVal)
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layout = robotpy_apriltag.AprilTagFieldLayout.loadField(
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robotpy_apriltag.AprilTagField.k2024Crescendo
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)
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self.objectInField = layout.getTagPose(0) or wpimath.Pose3d()
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self.fieldSim = wpilib.Field2d()
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self.fieldApproximation = wpilib.Field2d()
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# Here we use DifferentialDrivePoseEstimator so that we can fuse odometry readings. The
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# numbers used below are robot specific, and should be tuned.
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self.poseEstimator = wpimath.DifferentialDrivePoseEstimator(
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self.kinematics,
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self.imu.getRotation2d(),
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self.leftEncoder.getDistance(),
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self.rightEncoder.getDistance(),
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wpimath.Pose2d(),
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(0.05, 0.05, wpimath.units.degreesToRadians(5)),
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(0.5, 0.5, wpimath.units.degreesToRadians(30)),
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)
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# Gains are for example purposes only - must be determined for your own robot!
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self.feedforward = wpimath.SimpleMotorFeedforwardMeters(1, 3)
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# Simulation classes
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self.leftEncoderSim = wpilib.simulation.EncoderSim(self.leftEncoder)
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self.rightEncoderSim = wpilib.simulation.EncoderSim(self.rightEncoder)
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self.drivetrainSystem = wpimath.Models.differentialDriveFromSysId(
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1.98, 0.2, 1.5, 0.3
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)
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self.drivetrainSimulator = wpilib.simulation.DifferentialDrivetrainSim(
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self.drivetrainSystem,
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self.kTrackwidth,
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wpimath.DCMotor.CIM(2),
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8,
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self.kWheelRadius,
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)
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self.imu.resetYaw()
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self.leftLeader.addFollower(self.leftFollower)
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self.rightLeader.addFollower(self.rightFollower)
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# We need to invert one side of the drivetrain so that positive voltages
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# result in both sides moving forward. Depending on how your robot's
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# gearbox is constructed, you might have to invert the left side instead.
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self.rightLeader.setInverted(True)
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# Set the distance per pulse for the drive encoders. We can simply use the
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# distance traveled for one rotation of the wheel divided by the encoder
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# resolution.
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self.leftEncoder.setDistancePerPulse(
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math.tau * self.kWheelRadius / self.kEncoderResolution
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)
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self.rightEncoder.setDistancePerPulse(
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math.tau * self.kWheelRadius / self.kEncoderResolution
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)
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self.leftEncoder.reset()
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self.rightEncoder.reset()
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wpilib.SmartDashboard.putData("Field", self.fieldSim)
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wpilib.SmartDashboard.putData("FieldEstimation", self.fieldApproximation)
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def setSpeeds(self, speeds: wpimath.DifferentialDriveWheelSpeeds) -> None:
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"""Sets the desired wheel speeds.
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:param speeds: The desired wheel speeds.
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"""
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leftFeedforward = self.feedforward.calculate(speeds.left)
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rightFeedforward = self.feedforward.calculate(speeds.right)
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leftOutput = self.leftPIDController.calculate(
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self.leftEncoder.getRate(), speeds.left
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)
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rightOutput = self.rightPIDController.calculate(
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self.rightEncoder.getRate(), speeds.right
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)
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self.leftLeader.setVoltage(leftOutput + leftFeedforward)
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self.rightLeader.setVoltage(rightOutput + rightFeedforward)
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def drive(self, xSpeed: float, rot: float) -> None:
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"""Drives the robot with the given linear velocity and angular velocity.
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:param xSpeed: Linear velocity in m/s.
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:param rot: Angular velocity in rad/s.
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"""
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wheelSpeeds = self.kinematics.toWheelSpeeds(
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wpimath.ChassisSpeeds(xSpeed, 0.0, rot)
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)
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self.setSpeeds(wheelSpeeds)
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def publishCameraToObject(
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self,
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objectInField: wpimath.Pose3d,
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robotToCamera: wpimath.Transform3d,
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cameraToObjectEntry: ntcore.DoubleArrayEntry,
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drivetrainSimulator: wpilib.simulation.DifferentialDrivetrainSim,
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) -> None:
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"""Computes and publishes to a network tables topic the transformation from the
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camera's pose to the object's pose. This function exists solely for the
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purposes of simulation, and this would normally be handled by computer vision.
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The object could be a target or a fiducial marker.
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:param objectInField: The object's field-relative position.
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:param robotToCamera: The transformation from the robot's pose to the camera's pose.
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:param cameraToObjectEntry: The networktables entry publishing and querying example
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computer vision measurements.
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"""
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robotInField = wpimath.Pose3d(drivetrainSimulator.getPose())
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cameraInField = robotInField.transformBy(robotToCamera)
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cameraToObject = wpimath.Transform3d(cameraInField, objectInField)
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# Publishes double array with Translation3D elements {x, y, z} and Rotation3D elements
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# {w, x, y, z} which describe the cameraToObject transformation.
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quaternion = cameraToObject.rotation().getQuaternion()
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val = [
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cameraToObject.x,
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cameraToObject.y,
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cameraToObject.z,
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quaternion.w,
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quaternion.x,
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quaternion.y,
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quaternion.z,
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]
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cameraToObjectEntry.set(val)
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def objectToRobotPose(
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self,
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objectInField: wpimath.Pose3d,
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robotToCamera: wpimath.Transform3d,
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cameraToObjectEntry: ntcore.DoubleArrayEntry,
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) -> wpimath.Pose3d:
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"""Queries the camera-to-object transformation from networktables to compute the robot's
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field-relative pose from vision measurements.
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The object could be a target or a fiducial marker.
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:param objectInField: The object's field-relative pose.
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:param robotToCamera: The transformation from the robot's pose to the camera's pose.
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:param cameraToObjectEntry: The networktables entry publishing and querying example
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computer vision measurements.
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"""
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val = cameraToObjectEntry.get()
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# Reconstruct cameraToObject Transform3d from networktables.
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translation = wpimath.Translation3d(val[0], val[1], val[2])
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rotation = wpimath.Rotation3d(
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wpimath.Quaternion(val[3], val[4], val[5], val[6])
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)
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cameraToObject = wpimath.Transform3d(translation, rotation)
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cameraInField = objectInField.transformBy(cameraToObject.inverse())
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robotInField = cameraInField.transformBy(robotToCamera.inverse())
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return robotInField
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def updateOdometry(self) -> None:
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"""Updates the field-relative position."""
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self.poseEstimator.update(
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self.imu.getRotation2d(),
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self.leftEncoder.getDistance(),
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self.rightEncoder.getDistance(),
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)
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# Publish cameraToObject transformation to networktables --this would normally be handled by
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# the computer vision solution.
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self.publishCameraToObject(
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self.objectInField,
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self.robotToCamera,
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self.cameraToObjectEntry,
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self.drivetrainSimulator,
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)
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# Compute the robot's field-relative position exclusively from vision measurements.
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visionMeasurement3d = self.objectToRobotPose(
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self.objectInField, self.robotToCamera, self.cameraToObjectEntry
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)
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# Convert robot pose from Pose3d to Pose2d needed to apply vision measurements.
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visionMeasurement2d = visionMeasurement3d.toPose2d()
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# Apply vision measurements. For simulation purposes only, we don't input a latency delay --
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# on a real robot, this must be calculated based either on known latency or timestamps.
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self.poseEstimator.addVisionMeasurement(
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visionMeasurement2d,
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wpilib.Timer.getTimestamp(),
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)
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def simulationPeriodic(self) -> None:
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"""This function is called periodically during simulation."""
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# To update our simulation, we set motor voltage inputs, update the
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# simulation, and write the simulated positions and velocities to our
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# simulated encoder and gyro.
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self.drivetrainSimulator.setInputs(
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self.leftLeader.get() * wpilib.RobotController.getInputVoltage(),
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self.rightLeader.get() * wpilib.RobotController.getInputVoltage(),
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)
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self.drivetrainSimulator.update(0.02)
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self.leftEncoderSim.setDistance(self.drivetrainSimulator.getLeftPosition())
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self.leftEncoderSim.setRate(self.drivetrainSimulator.getLeftVelocity())
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self.rightEncoderSim.setDistance(self.drivetrainSimulator.getRightPosition())
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self.rightEncoderSim.setRate(self.drivetrainSimulator.getRightVelocity())
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# self.gyroSim.setAngle(-self.drivetrainSimulator.getHeading().getDegrees())
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def periodic(self) -> None:
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"""This function is called periodically, no matter the mode."""
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self.updateOdometry()
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self.fieldSim.setRobotPose(self.drivetrainSimulator.getPose())
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self.fieldApproximation.setRobotPose(self.poseEstimator.getEstimatedPosition())
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