XTDrone/sensing/slam/vio/VINS-Fusion/config/simulation/simulation_config.yaml

67 lines
2.5 KiB
YAML

%YAML:1.0
#common parameters
imu: 1
num_of_cam: 2 # 1 or 2
imu_topic: "/data_generator/imu"
image0_topic: "/cam0/image_raw"
image1_topic: "/cam1/image_raw"
output_path: "/home/tony-ws1/output/"
cam0_calib: "cam0_mei.yaml"
cam1_calib: "cam1_mei.yaml"
image_width: 600
image_height: 600
# 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.
#cam0 to body
body_T_cam0: !!opencv-matrix
rows: 4
cols: 4
dt: d
data: [0, 0, -1, -0.02,
-1, 0, 0, 0,
0, 1, 0, 0.02,
0, 0, 0, 1]
#cam1 to body
body_T_cam1: !!opencv-matrix
rows: 4
cols: 4
dt: d
data: [0, 0, -1, 0,
-1, 0, 0, 0,
0, 1, 0, 0.3,
0, 0, 0, 1]
#Multiple thread support
multiple_thread: 0
#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: 0.2 # accelerometer measurement noise standard deviation. #0.2
gyr_n: 0.02 # gyroscope measurement noise standard deviation. #0.05
acc_w: 0.0002 # accelerometer bias random work noise standard deviation. #0.02
gyr_w: 2.0e-5 # gyroscope bias random work noise standard deviation. #4.0e-5
g_norm: 9.805 # gravity magnitude
#unsynchronization parameters
estimate_td: 0 # 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)
#visualization parameters
save_image: 0 # 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