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mynteye_s_config.yaml
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mynteye_s_config.yaml
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%YAML:1.0
#common parameters
imu_topic: "/mynteye/imu/data_raw"
image_topic: "/mynteye/left/image_raw"
output_path: "/home/zhangs/mynt_vins/config/mynteye"
#camera calibration, please replace it with your own calibration file.
#model_type: MEI
#camera_name: camera
#image_width: 752
#image_height: 480
#mirror_parameters:
# xi: 2.3240502152083149e+00
#distortion_parameters:
# k1: -7.2846074363884863e-02
# k2: 7.3922066251669893e-01
# p1: 7.8031450490717439e-04
# p2: 1.1125751544447434e-04
#projection_parameters:
# gamma1: 1.1919574208429231e+03
# gamma2: 1.1962419519374005e+03
# u0: 3.9017559066380522e+02
# v0: 2.5308889949771191e+02
model_type: PINHOLE
camera_name: camera
image_width: 752
image_height: 480
distortion_parameters:
k1: -3.0825216120347504e-01
k2: 8.4251305214302186e-02
p1: -1.5009319710179576e-04
p2: 2.0170689406091280e-04
projection_parameters:
fx: 3.5847442850029023e+02
fy: 3.5952665535350462e+02
cx: 3.8840661559633401e+02
cy: 2.5476941553631312e+02
# Extrinsic parameter between IMU and Camera.
estimate_extrinsic: 0 # 0 Have an accurate extrinsic parameters. We will trust the following imu^R_cam, imu^T_cam, don't change it.
# 1 Have an initial guess about extrinsic parameters. We will optimize around your initial guess.
# 2 Don't know anything about extrinsic parameters. You don't need to give R,T. We will try to calibrate it. Do some rotation movement at beginning.
#If you choose 0 or 1, you should write down the following matrix.
#Rotation from camera frame to imu frame, imu^R_cam
extrinsicRotation: !!opencv-matrix
rows: 3
cols: 3
dt: d
data: [-0.0064662, -0.99994994, -0.00763565,
0.99997909, -0.00646566, -0.00009558,
0.0000462, -0.00763611, 0.99997084]
#Translation from camera frame to imu frame, imu^T_cam
extrinsicTranslation: !!opencv-matrix
rows: 3
cols: 1
dt: d
data: [0.00533646,-0.04302922, 0.02303124]
#feature traker paprameters
max_cnt: 150 # max feature number in feature tracking
min_dist: 30 # min distance between two features
freq: 10 # frequence (Hz) of publish tracking result. At least 10Hz for good estimation. If set 0, the frequence will be same as raw image
F_threshold: 1.0 # ransac threshold (pixel)
show_track: 1 # publish tracking image as topic
equalize: 1 # if image is too dark or light, trun on equalize to find enough features
fisheye: 0 # if using fisheye, trun on it. A circle mask will be loaded to remove edge noisy points
#optimization parameters
max_solver_time: 0.04 # max solver itration time (ms), to guarantee real time
max_num_iterations: 8 # max solver itrations, to guarantee real time
keyframe_parallax: 10.0 # keyframe selection threshold (pixel)
#imu parameters The more accurate parameters you provide, the better performance
acc_n: 0.0268014618074 # accelerometer measurement noise standard deviation. #0.599298904976
gyr_n: 0.00888232829671 # gyroscope measurement noise standard deviation. #0.198614898699
acc_w: 0.00262960861593 # accelerometer bias random work noise standard deviation. #0.02
gyr_w: 0.000379565782927 # gyroscope bias random work noise standard deviation. #4.0e-5
#imu parameters The more accurate parameters you provide, the better performance
#acc_n: 7.6509e-02 # accelerometer measurement noise standard deviation. #0.599298904976
#gyr_n: 9.0086e-03 # gyroscope measurement noise standard deviation. #0.198614898699
#acc_w: 5.3271e-02 # accelerometer bias random work noise standard deviation. #0.02
#gyr_w: 5.5379e-05 # gyroscope bias random work noise standard deviation. #4.0e-5
g_norm: 9.81007 # gravity magnitude
#loop closure parameters
loop_closure: 1 # start loop closure
load_previous_pose_graph: 0 # load and reuse previous pose graph; load from 'pose_graph_save_path'
fast_relocalization: 0 # useful in real-time and large project
pose_graph_save_path: "/home/zhangs/mynt_vins/config/mynteye/pose_graph/" # save and load path
#unsynchronization parameters
estimate_td: 1 # online estimate time offset between camera and imu
td: 0.0 # initial value of time offset. unit: s. readed image clock + td = real image clock (IMU clock)
#rolling shutter parameters
rolling_shutter: 0 # 0: global shutter camera, 1: rolling shutter camera
rolling_shutter_tr: 0 # unit: s. rolling shutter read out time per frame (from data sheet).
#visualization parameters
save_image: 1 # save image in pose graph for visualization prupose; you can close this function by setting 0
visualize_imu_forward: 0 # output imu forward propogation to achieve low latency and high frequence results
visualize_camera_size: 0.4 # size of camera marker in RVIZ