VINS（二）Feature Detection and Tracking

imu_topic: "/imu0"
image_topic: "/cam0/image_raw"

image_width: 752
image_height: 480

#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: 9.81007     # gravity magnitude

# 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. 

#loop closure parameters
loop_closure: 1   #if you want to use loop closure to minimize the drift, set loop_closure true and give your brief pattern file path and vocabulary file path accordingly;
                     #also give the camera calibration file same as feature_tracker node
pattern_file: "/support_files/brief_pattern.yml"
voc_file: "/support_files/brief_k10L6.bin"
min_loop_num: 25