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 ```