AprilTag

2. Vision Coprocessor Setup

2.1 Initial Hardware Setup

1. Coprocessor Preparation:
2. Make sure your coprocessor is already set up from a previous quickstart, OR
3. Download latest Orange PI 5 PhotonVision image
4. Flash image to microSD card

5. Insert microSD into Orange PI 5

6. Camera Naming:

   • Download ArducamUVCSerialNumber_Official.zip
   • Extract the program
   • For each Arducam OV9281 camera:
     1. Connect camera to laptop via USB
     2. Open ArducamUVCSerialNumber program
     3. In "Device name" field, enter camera position:
        • Format: POSITION_AprilTag
        • Examples: FL_AprilTag, FM_AprilTag, FR_AprilTag
     4. Click "Write"
     5. Open Device Manager
     6. Uninstall the camera
     7. Reconnect the camera
     8. Verify new name appears
     9. Disconnect from laptop
     10. Connect to Orange PI 5
   • Repeat for all cameras

2.2 PhotonVision Configuration

1. Pipeline Setup:

   • Open PhotonVision web interface
   • For each camera:
     1. Select camera in UI
     2. Create new pipeline named "AprilTag"
     3. Set pipeline type to "AprilTag"
     4. Configure processing:
        • Decimate: 2
        • Blur: 1
        • Auto White Balance: ON
     5. Set camera settings:
        • Resolution: 1280x720
        • FPS: 100 (or similar)
        • Stream Resolution: Lowest available
     6. Navigate to Cameras tab
     7. Select camera
     8. Set Model as "OV9281"

2. Camera Calibration:

   • For each camera:
     1. Select calibration settings:
        • Tag Family: 5x5
        • Resolution: 720p
        • Pattern Spacing: 3.15 inches
        • Marker Size: 2.36 inches
        • Board: 12x8
     2. Take multiple calibration snapshots:
        • Vary angles and distances
        • Include corner views
        • Mix close and far positions
     3. Run calibration
     4. Verify mean error < 1.0 pixels
     5. If error too high:
        • Delete poor quality snapshots
        • Add more varied angles
        • Recalibrate

3. Final Configuration:

   • For each pipeline:
     1. Enable 3D mode
     2. Enable multi-tag detection
     3. Save settings

4. Field Tuning:

   • At competition field:
     • Adjust exposure
     • Tune brightness
     • Set appropriate gain
     • Test detection reliability

     • Save field-specific settings

2.3 Camera Offset Measurement

Accurate camera position measurements are critical for AprilTag vision:

1. Physical Measurements:

   • Use calipers or precise measuring tools
   • Measure from robot center (origin) to camera lens center
   • Record three distances for each camera:
     • Forward distance (X): positive towards robot front
     • Left distance (Y): positive towards robot left
     • Up distance (Z): positive towards robot top
   • Measure camera angles:
     • Pitch: downward tilt (usually negative)
     • Yaw: left/right rotation

2. Update Constants:

   private static final Transform3d[] CAMERA_OFFSETS = new Transform3d[] {
       // Front Left Camera
       new Transform3d(
           new Translation3d(0.245, 0.21, 0.17),  // X, Y, Z in meters
           new Rotation3d(0, Math.toRadians(-35), Math.toRadians(45))),  // Roll, Pitch, Yaw
   
       // Front Middle Camera
       new Transform3d(
           new Translation3d(0.275, 0.0, 0.189),
           new Rotation3d(0, Math.toRadians(-35), Math.toRadians(0)))
   };
   

3. Camera Configuration:

   // Add configuration for each physical camera
   private static final CameraConfig[] CAMERA_CONFIGS = new CameraConfig[] {
       new CameraConfig("FL_AprilTag", CAMERA_OFFSETS[0], new SimCameraProperties()),
       new CameraConfig("FM_AprilTag", CAMERA_OFFSETS[1], new SimCameraProperties())
   };
   

4. IO Configuration:

   // In RobotContainer.java constructor:
   aprilTagSubsystem =
           new AprilTagSubsystem(
               swerveDriveSubsystem::addVisionMeasurement,
               new AprilTagIOPhotonVision(AprilTagConstants.CAMERA_CONFIGS[0]),
               new AprilTagIOPhotonVision(AprilTagConstants.CAMERA_CONFIGS[1]));
   

5. Replay Support:

   // For replay mode, match array size to physical cameras
   aprilTagSubsystem =
           new AprilTagSubsystem(
               swerveDriveSubsystem::addVisionMeasurement,
               new AprilTagIO() {},
               new AprilTagIO() {});
   

2.4 Camera Verification

After configuring camera offsets:

1. Physical Checks:

   • Verify camera mounts are secure
   • Check USB connections
   • Confirm cameras are powered
   • LED indicators should be on

2. Network Verification:

   • Open PhotonVision dashboard
   • Confirm all cameras are connected
   • Check video feeds are active
   • Verify camera names match configs

3. Basic Testing:

   • Hold AprilTag in camera view
   • Confirm detection in dashboard
   • Check pose estimation quality
   • Verify reasonable distance estimates

4. Optional Camera Tuning:

   • Camera Trust Factors:

     // Standard deviation multipliers for each camera
     // (Adjust to trust some cameras more than others)
     // SHOULD NEVER BE LESS THAN 1.0, NUMBERS GREATER THAN 1 = TRUST LESS
     public static double[] CAMERA_STD_DEV_FACTORS = new double[] {1.0, 1.0};
     

     • Higher values = trust that camera less
     • Example: {1.0, 1.5} trusts first camera more than second
     • Never use values less than 1.0
     • Useful when some cameras are more reliable than others

   • Ambiguity Filtering:

     public static double MAX_AMBIGUITY = 0.3;
     

     • Filters out less confident tag detections
     • Lower values = stricter filtering
     • Range 0.0 to 1.0
     • Start with 0.3 and adjust based on false positive rate

5. Common Issues:

   • Camera disconnections: Check USB connections
   • Poor detection: Adjust exposure/brightness
   • Incorrect poses: Double-check offset measurements
   • Network lag: Monitor bandwidth usage