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Yaml formats
##Camera system configuration (aka chain.yaml)
describe all the possible entries...
- camera_model
- time
- to imu
- to last
chain evtl bild imu0 -> cam0 -> cam1 -> cam2
link intrinsics vector to camera models --> omni -> 5 -> [xi fu....]
chain.yaml
cam0:
camera_model: omni
distortion_coeffs: [-0.3524047797899213, 0.16207450943423096, 0.00036919741711283124,
0.000988523976270618]
distortion_model: radtan
intrinsics: [0.671111239995445, 770.7765589675081, 770.5559465743702, 362.1635863019238,
247.88842203540298]
resolution: [752, 480]
rostopic: /cam0/image_raw
cam1:
baseline_last_to_this_cam:
- [0.9999963219239997, 0.002667912895867444, 0.00048824097823761936, -0.10998811687147413]
- [-0.0026721458237613386, 0.9999569589497798, 0.008884812018572488, 0.0003133265658200174]
- [-0.0004645160592714478, -0.008886083990649619, 0.9999604100843904, -0.00041422980563141245]
- [0.0, 0.0, 0.0, 1.0]
camera_model: omni
distortion_coeffs: [-0.34330808866302887, 0.14844603008818044, -0.0003074632859414297,
0.0013186394350600886]
distortion_model: radtan
intrinsics: [0.7476616047651173, 805.0992800974523, 805.1201800399643, 376.61967341034676,
256.0786828765575]
resolution: [752, 480]
rostopic: /cam1/image_raw
INTRODUCE BETTER TRAFO NAMES ...
##IMU configuration Each IMU in the calibration is configured using a YAML file. Please refer to the example below for details:
imu0.yaml
#Accelerometers
accelerometer_noise_density: 0.006 #Noise density (continous) [UNIT]
accelerometer_random_walk: 0.0002 #Bias random walk [UNIT]
#Gyroscopes
gyroscope_noise_density: 0.0004 #Noise density (continous) [UNIT]
gyroscope_random_walk: 4.0e-06 #Bias random walk [UNIT]
update_rate: 200.0 #Hz (used for discretization of the above values)
INSERT UNITS ABOVE!
##Calibration target configuration Please refer to the Calibration targets page.
Multiple camera calibration
Camera-IMU calibration
Multi-IMU and IMU intrinsic calibration
Rolling Shutter camera calibration
(only ROS):
Camera focus
Calibration validator
ROS2 support
Supported camera models
Calibration targets
Bag format
YAML formats
IMU Noise Model
Example: Calibrating a VI-Sensor
Example: Calibrating RealSense Cameras