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2025RidgeScape/src/main/java/frc4388/robot/subsystems/Vision.java
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package frc4388.robot.subsystems;
import edu.wpi.first.math.Matrix;
import edu.wpi.first.math.VecBuilder;
import edu.wpi.first.math.geometry.Pose2d;
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import edu.wpi.first.math.geometry.Rotation2d;
import edu.wpi.first.math.geometry.Transform3d;
import edu.wpi.first.math.geometry.Translation2d;
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import edu.wpi.first.math.numbers.N1;
import edu.wpi.first.math.numbers.N3;
import java.util.List;
import java.util.Optional;
import org.photonvision.EstimatedRobotPose;
import org.photonvision.PhotonCamera;
import org.photonvision.PhotonPoseEstimator;
import org.photonvision.PhotonPoseEstimator.PoseStrategy;
import org.photonvision.simulation.PhotonCameraSim;
import org.photonvision.simulation.SimCameraProperties;
import org.photonvision.simulation.VisionSystemSim;
import org.photonvision.targeting.MultiTargetPNPResult;
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import org.photonvision.targeting.PhotonTrackedTarget;
import com.ctre.phoenix6.Utils;
import edu.wpi.first.networktables.GenericEntry;
import edu.wpi.first.wpilibj.shuffleboard.BuiltInLayouts;
import edu.wpi.first.wpilibj.shuffleboard.BuiltInWidgets;
import edu.wpi.first.wpilibj.shuffleboard.Shuffleboard;
import edu.wpi.first.wpilibj.shuffleboard.ShuffleboardLayout;
import edu.wpi.first.wpilibj.smartdashboard.Field2d;
import edu.wpi.first.wpilibj.smartdashboard.SmartDashboard;
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import frc4388.robot.Constants.FieldConstants;
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import frc4388.robot.Constants.VisionConstants;
import frc4388.utility.Status;
import frc4388.utility.Subsystem;
public class Vision extends Subsystem {
private PhotonCamera camera;
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private boolean isTagDetected = false;
private boolean isTagProcessed = false;
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private Pose2d lastVisionPose = new Pose2d();
private Pose2d lastPhysOdomPose = new Pose2d();
private Matrix<N3, N1> curStdDevs;
private final PhotonPoseEstimator photonEstimator;
private Field2d field = new Field2d();
ShuffleboardLayout subsystemLayout = Shuffleboard.getTab("Subsystems")
.getLayout(getSubsystemName(), BuiltInLayouts.kList)
.withSize(2, 2);
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GenericEntry sbTagDetected = subsystemLayout
.add("Tag Detected", false)
.withWidget(BuiltInWidgets.kBooleanBox)
.getEntry();
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GenericEntry sbTagProcessed = subsystemLayout
.add("Tag Processed", false)
.withWidget(BuiltInWidgets.kBooleanBox)
.getEntry();
GenericEntry sbCamConnected = subsystemLayout
.add("Camera Connnected", false)
.withWidget(BuiltInWidgets.kBooleanBox)
.getEntry();
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public Vision(PhotonCamera camera){
this.camera = camera;
SmartDashboard.putData(field);
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photonEstimator = new PhotonPoseEstimator(FieldConstants.kTagLayout, PoseStrategy.MULTI_TAG_PNP_ON_COPROCESSOR, VisionConstants.CAMERA_POS);
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photonEstimator.setMultiTagFallbackStrategy(PoseStrategy.LOWEST_AMBIGUITY);
}
@Override
public void periodic() {
var result = camera.getLatestResult();
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// var results = camera.getAllUnreadResults();
// if (results.size() == 0) return;
// var result = results.get(results.size()-1);
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isTagDetected = result.hasTargets();
isTagProcessed = false;
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// Optional<MultiTargetPNPResult> multitag = result.getMultiTagResult();
// if (multitag.isEmpty()) {
// Transform3d fieldToCamera = result.getMultiTagResult().estimatedPose.best;
// }else if()
// sbTag.setBoolean(isTag);
// field.setRobotPose(getPose2d());
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// sbCamConnected.setBoolean(camera);
// System.out.println(isTag);
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if(!isTagDetected){
// sbTagDetected.setBoolean(isTagDetected);
field.setRobotPose(getPose2d());
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return;
}
var EstimatedRobotPose = getEstimatedGlobalPose();
// In case the pose estimator fails to estimate the pose, fallback to physical odometry.
if(EstimatedRobotPose.isEmpty()){
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// sbTagProcessed.setBoolean(isTagProcessed);
field.setRobotPose(lastVisionPose);
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return;
}
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isTagProcessed = true;
lastVisionPose = EstimatedRobotPose.get().estimatedPose.toPose2d();
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// lastVisionPose.rotateBy(Rotation2d.k180deg);
// lastVisionPose = new Pose2d(
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// lastVisionPose.getTranslation(),
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// lastPhysOdomPose.getRotation()
// );
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field.setRobotPose(getPose2d());
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}
/**
* The latest estimated robot pose on the field from vision data. This may be empty. This should
* only be called once per loop.
*
* <p>Also includes updates for the standard deviations, which can (optionally) be retrieved with
* {@link getEstimationStdDevs}
*
* @return An {@link EstimatedRobotPose} with an estimated pose, estimate timestamp, and targets
* used for estimation.
*/
public Optional<EstimatedRobotPose> getEstimatedGlobalPose() {
Optional<EstimatedRobotPose> visionEst = Optional.empty();
for (var change : camera.getAllUnreadResults()) {
visionEst = photonEstimator.update(change);
updateEstimationStdDevs(visionEst, change.getTargets());
// if (Robot.isSimulation()) {
// visionEst.ifPresentOrElse(
// est ->
// getSimDebugField()
// .getObject("VisionEstimation")
// .setPose(est.estimatedPose.toPose2d()),
// () -> {
// getSimDebugField().getObject("VisionEstimation").setPoses();
// });
// }
}
return visionEst;
}
/**
* Calculates new standard deviations This algorithm is a heuristic that creates dynamic standard
* deviations based on number of tags, estimation strategy, and distance from the tags.
*
* @param estimatedPose The estimated pose to guess standard deviations for.
* @param targets All targets in this camera frame
*/
private void updateEstimationStdDevs(
Optional<EstimatedRobotPose> estimatedPose, List<PhotonTrackedTarget> targets) {
if (estimatedPose.isEmpty()) {
// No pose input. Default to single-tag std devs
curStdDevs = VisionConstants.kSingleTagStdDevs;
} else {
// Pose present. Start running Heuristic
var estStdDevs = VisionConstants.kSingleTagStdDevs;
int numTags = 0;
double avgDist = 0;
// Precalculation - see how many tags we found, and calculate an average-distance metric
for (var tgt : targets) {
var tagPose = photonEstimator.getFieldTags().getTagPose(tgt.getFiducialId());
if (tagPose.isEmpty()) continue;
numTags++;
avgDist +=
tagPose
.get()
.toPose2d()
.getTranslation()
.getDistance(estimatedPose.get().estimatedPose.toPose2d().getTranslation());
}
if (numTags == 0) {
// No tags visible. Default to single-tag std devs
curStdDevs = VisionConstants.kSingleTagStdDevs;
} else {
// One or more tags visible, run the full heuristic.
avgDist /= numTags;
// Decrease std devs if multiple targets are visible
if (numTags > 1) estStdDevs = VisionConstants.kMultiTagStdDevs;
// Increase std devs based on (average) distance
if (numTags == 1 && avgDist > 4)
estStdDevs = VecBuilder.fill(Double.MAX_VALUE, Double.MAX_VALUE, Double.MAX_VALUE);
else estStdDevs = estStdDevs.times(1 + (avgDist * avgDist / 30));
curStdDevs = estStdDevs;
}
}
}
/**
* Returns the latest standard deviations of the estimated pose from {@link
* #getEstimatedGlobalPose()}, for use with {@link
* edu.wpi.first.math.estimator.SwerveDrivePoseEstimator SwerveDrivePoseEstimator}. This should
* only be used when there are targets visible.
*/
public Matrix<N3, N1> getEstimationStdDevs() {
return curStdDevs;
}
public void setLastOdomPose(Optional<Pose2d> pose){
if(pose.isPresent())
lastPhysOdomPose = pose.get();
}
public Pose2d getPose2d() {
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if(isTagDetected && isTagProcessed)
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return lastVisionPose;
else
return lastPhysOdomPose;
}
public static double getTime() {
return Utils.getCurrentTimeSeconds();
}
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public boolean isTag(){
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return isTagDetected && isTagProcessed;
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}
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@Override
public String getSubsystemName() {
return "Vision";
}
// GenericEntry sbShiftState = subsystemLayout
// .add("Shift State", 0)
// .withWidget(BuiltInWidgets.kNumberBar)
// .getEntry();
@Override
public void queryStatus() {
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sbTagDetected.setBoolean(isTagDetected);
sbTagProcessed.setBoolean(isTagProcessed);
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sbCamConnected.setBoolean(camera.isConnected());
// field.setRobotPose(getPose2d());
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}
@Override
public Status diagnosticStatus() {
Status status = new Status();
return status;
}
}