camera param
===
###### tags: `NSPO`
```
%YAML:1.0
#common parameters
imu_topic: "/mavros/imu/data_raw"
image_topic: "/arducam/triggered/camera/image_raw"
output_path: "/home/ncrl/catkin_ws1/src/VINS-Mono/support_files"
#camera calibration
model_type: PINHOLE
camera_name: camera
#AR0134_M25360H06
image_width: 640
image_height: 484
distortion_parameters:
k1: -0.347793
k2: 0.107340
p1: 0.000722
p2: -0.001039
projection_parameters:
fx: 416.811266
fy: 417.101651
cx: 316.940768
cy: 251.243429
#MT9v034_LS301188
#image_width: 640
#image_height: 480
#distortion_parameters:
# k1: -0.35756
# k2: 0.11909
# p1: -0.001066
# p2: -0.001789
#projection_parameters:
# fx: 450.946511
# fy: 453.592795
# cx: 297.75849
# cy: 255.72969
# Extrinsic parameter between IMU and Camera.
estimate_extrinsic: 1 # 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, 0, 1,
-1, 0, 0,
0, -1, 0]
#Translation from camera frame to imu frame, imu^T_cam
extrinsicTranslation: !!opencv-matrix
rows: 3
cols: 1
dt: d
data: [0.10, 0, -0.10]
#feature traker paprameters
max_cnt: 100 # max feature number in feature tracking
min_dist: 25 # 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
#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: 0.08 # accelerometer measurement noise standard deviation. #0.2 0.04
#gyr_n: 0.004 # gyroscope measurement noise standard deviation. #0.05 0.004
acc_n: 0.4 # accelerometer measurement noise standard deviation. #0.2 0.04
gyr_n: 0.05 # gyroscope measurement noise standard deviation. #0.05 0.004
acc_w: 0.04 # accelerometer bias random work noise standard deviation. #0.02
gyr_w: 4.0e-5 # gyroscope bias random work noise standard deviation. #4.0e-5
g_norm: 9.805 # gravity magnitude
#loop closure parameters
loop_closure: 0 # start loop closure
fast_relocalization: 1 # useful in real-time and large project
load_previous_pose_graph: 0 # load and reuse previous pose graph; load from 'pose_graph_save_path'
pose_graph_save_path: "/home/ncrl/catkin_ws1/src/VINS-Mono/support_files" # save and load path
#unsynchronization parameters
estimate_td: 1 # online estimate time offset between camera and imu
td: -0.04 # 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: 1 # output imu forward propogation to achieve low latency and high frequence results
visualize_camera_size: 0.4 # size of camera marker in RVIZ
```