ROS2-ORB-SLAM3/Examples_old/Stereo-Inertial/RealSense_T265.yaml

%YAML:1.0

#--------------------------------------------------------------------------------------------
# Camera Parameters. Adjust them!
#--------------------------------------------------------------------------------------------
Camera.type: "KannalaBrandt8"

# Left Camera calibration and distortion parameters (OpenCV)
Camera.fx: 284.9501953125
Camera.fy: 285.115295410156
Camera.cx: 420.500213623047
Camera.cy: 400.738098144531

# Kannala-Brandt distortion parameters
Camera.k1: -0.00530046410858631
Camera.k2: 0.0423333682119846
Camera.k3: -0.03949885815382
Camera.k4: 0.00682387687265873

# Right Camera calibration and distortion parameters (OpenCV)
Camera2.fx: 285.001312255859
Camera2.fy: 284.914215087891
Camera2.cx: 411.864196777344
Camera2.cy: 403.41259765625

# Kannala-Brandt distortion parameters
Camera2.k1: -0.00375203299336135
Camera2.k2: 0.0379297286272049
Camera2.k3: -0.0352463386952877
Camera2.k4: 0.00548873096704
    
# Transformation matrix from right camera to left camera
Tlr: !!opencv-matrix
  rows: 3
  cols: 4
  dt: f
  data: [ 0.999983, 0.00445005, 0.00385861, 0.0636739954352379,
            -0.00443664, 0.999984, -0.00347621, -0.000252007856033742,
            -0.00387402, 0.00345903, 0.999986, -8.87895439518616e-05]

# Lapping area between images (We must calculate)
Camera.lappingBegin: 0
Camera.lappingEnd: 848 

Camera2.lappingBegin: 0
Camera2.lappingEnd: 848

# Camera resolution
Camera.width: 848
Camera.height: 800

# Camera frames per second 
Camera.fps: 30.0

# Color order of the images (0: BGR, 1: RGB. It is ignored if images are grayscale)
Camera.RGB: 1

# Image scale, it changes the image size to be processed (<1.0: reduce, >1.0: increase)
Camera.imageScale: 0.5 # 0.7071 # 1/sqrt(2)

# Close/Far threshold. Baseline times.
ThDepth: 40.0
# stereo baseline times fx
Camera.bf: 18.143917436


# Transformation from body-frame (imu) to left camera
Tbc: !!opencv-matrix
   rows: 4
   cols: 4
   dt: f
   data: [-0.999959, -0.00265193, 0.00870996, 0.0107000041753054, 
          0.00262197, -0.999991, -0.0034493, -1.45519152283669e-11,
         0.00871902, -0.00342632, 0.999956, -1.45519152283669e-11,
          0.0, 0.0, 0.0, 1.0]

# Do not insert KFs when recently lost
InsertKFsWhenLost: 0

# IMU noise
IMU.NoiseGyro: 1e-3 # 0.000005148030141 # rad/s^0.5 
IMU.NoiseAcc: 1e-2 # 0.000066952452471 # m/s^1.5
IMU.GyroWalk: 0.000000499999999 # rad/s^1.5
IMU.AccWalk: 0.000099999997474 # m/s^2.5
IMU.Frequency: 200

#--------------------------------------------------------------------------------------------
# ORB Parameters
#--------------------------------------------------------------------------------------------

# ORB Extractor: Number of features per image
ORBextractor.nFeatures: 500 # Tested with 1250

# ORB Extractor: Scale factor between levels in the scale pyramid 	
ORBextractor.scaleFactor: 1.2

# ORB Extractor: Number of levels in the scale pyramid	
ORBextractor.nLevels: 8

# ORB Extractor: Fast threshold
# Image is divided in a grid. At each cell FAST are extracted imposing a minimum response.
# Firstly we impose iniThFAST. If no corners are detected we impose a lower value minThFAST
# You can lower these values if your images have low contrast			
ORBextractor.iniThFAST: 15 # 20
ORBextractor.minThFAST: 7 # 7

#--------------------------------------------------------------------------------------------
# Viewer Parameters
#--------------------------------------------------------------------------------------------
Viewer.KeyFrameSize: 0.05
Viewer.KeyFrameLineWidth: 1
Viewer.GraphLineWidth: 0.9
Viewer.PointSize: 2
Viewer.CameraSize: 0.08
Viewer.CameraLineWidth: 3
Viewer.ViewpointX: 0
Viewer.ViewpointY: -0.7
Viewer.ViewpointZ: -3.5
Viewer.ViewpointF: 500
Viewer.imageViewScale: 2