.. _how_to_use_kalibr: How to calibrate MYNTEYE by kalibr =================================== Target ------------ * Calibrate the pose relationship between left and right camera * Calibrate the pose relationship left camera between and IMU Preparation ------------ * **Install kalibr**:Refer to `kalibr wiki `_ and follow the steps to install * **Calibration board**： kalibr supports ``chessbord`` , ``circlegrid`` , ``aprilgrid`` ,choose ``aprilgrid`` here Calibration board file can be directly `download `_ , Or you can also generate calibration board by Kalibr tool. .. code-block:: bash $ kalibr_create_target_pdf --type 'apriltag' --nx 6 --ny 6 --tsize 0.08 --tspace 0.3 View parameters' meanings by kalibr_create)target_pdf command: .. code-block:: bash $ kalibr_create_target_pdf --h usage: Example Aprilgrid: kalibr_create_target_pdf --type apriltag --nx 6 --ny 6 --tsize 0.08 --tspace 0.3 Example Checkerboard: kalibr_create_target_pdf --type checkerboard --nx 6 --ny 6 -csx 0.05 --csy 0.1 Generate PDFs of calibration patterns. optional arguments: -h, --help show this help message and exit Output options: output Output filename --eps Also output an EPS file Generic grid options: --type GRIDTYPE The grid pattern type. ('apriltag' or 'checkerboard') --nx N_COLS The number of tags in x direction (default: 6) --ny N_ROWS The number of tags in y direction (default: 7) Apriltag arguments: --tsize TSIZE The size of one tag [m] (default: 0.08) --tspace TAGSPACING The space between the tags in fraction of the edge size [0..1] (default: 0.3) --tfam TAGFAMILIY Familiy of April tags ['t16h5', 't25h9', 't25h7', 't36h11'] (default: t36h11) Checkerboard arguments: --csx CHESSSZX The size of one chessboard square in x direction [m] (default: 0.05) --csy CHESSSZY The size of one chessboard square in y direction [m] (default: 0.05) * **Calibrate the intrinsic IMU parameters** ：kalibr requires imu data to be calibrated by intrinsic parameters by default.The intrinsic parameters calibration tool uses `imu-tk `_ . * **Count imu data parameter**： * noise density * bias random walk Using Allan analyzing tool `imu_utils `_, We can get the characteristics of above imu data,and to format the output as ``imu.yaml`` .. code-block:: bash #Accelerometers accelerometer_noise_density: 0.02680146180736048 #Noise density (continuous-time) accelerometer_random_walk: 0.0026296086159332804 #Bias random walk #Gyroscopes gyroscope_noise_density: 0.008882328296710996 #Noise density (continuous-time) gyroscope_random_walk: 0.00037956578292701033 #Bias random walk rostopic: /mynteye/imu/data_raw #the IMU ROS topic update_rate: 200.0 #Hz (for discretization of the values above) Calibrate the pose relationship between left and right camera -------------------------------------------------------------- * Collect calibration images: kalibr supports the collection of the required calibration images through two ways:by ``rosbag`` or collect offline images . Using ``rosbag`` here for convenience,Reference `link `_ for collecting images. * Method of collecting images by ``rosbag`` :fix mynteye camera,move ``aprilgrid`` calibration board in the camera field of view. * To increase the calibration time,try to use image acquisition data with lower frame rate,kalibr recommends using ``4Hz`` frame rate,here uses ``10hz`` . * MYNTEYE S series camera offers images at least 10Hz,You can use `topic_tools `_ to modify frequency,because using 10Hz requires more calibration time. * Record ``static.bag`` : After fix the mynteye camera,start `wrapper `_, record the topic of the left and right images to ``static.bag`` . .. code-block:: bash $ source wrappers/ros/devel/setup.bash $ roslaunch mynt_eye_ros_wrapper display.launch $ cd ~ $ mkdir -p bag $ cd bag $ rosbag record -O static_10hz /mynteye/left/image_raw /mynteye/right/image_raw #recommand use 10hz,you can also use topic_tools to publish 4hz. * kalibr calibration: .. code-block:: bash $ kalibr_calibrate_cameras --target aprilgrid.yaml --bag ~/bag/static_10hz.bag --models pinhole-radtan pinhole-radtan --topics /mynteye/left/image_raw /mynteye/right/image_raw View parameters' meanings by kalibr_calibrate_cameras command: .. code-block:: bash $ kalibr_calibrate_cameras --h Calibrate the intrinsics and extrinsics of a camera system with non-shared overlapping field of view. usage: Example usage to calibrate a camera system with two cameras using an aprilgrid. cam0: omnidirection model with radial-tangential distortion cam1: pinhole model with equidistant distortion kalibr_calibrate_cameras --models omni-radtan pinhole-equi --target aprilgrid.yaml \ --bag MYROSBAG.bag --topics /cam0/image_raw /cam1/image_raw example aprilgrid.yaml: target_type: 'aprilgrid' tagCols: 6 tagRows: 6 tagSize: 0.088 #m tagSpacing: 0.3 #percent of tagSize optional arguments: -h, --help show this help message and exit --models MODELS [MODELS ...] The camera model ['pinhole-radtan', 'pinhole-equi', 'omni-radtan', 'pinhole-fov'] to estimate Data source: --bag BAGFILE The bag file with the data --topics TOPICS [TOPICS ...] The list of image topics --bag-from-to bag_from_to bag_from_to Use the bag data starting from up to this time [s] Calibration target configuration: --target TARGETYAML Calibration target configuration as yaml file Image synchronization: --approx-sync MAX_DELTA_APPROXSYNC Time tolerance for approximate image synchronization [s] (default: 0.02) Calibrator settings: --qr-tol QRTOL The tolerance on the factors of the QR decomposition (default: 0.02) --mi-tol MITOL The tolerance on the mutual information for adding an image. Higher means fewer images will be added. Use -1 to force all images. (default: 0.2) --no-shuffle Do not shuffle the dataset processing order Outlier filtering options: --no-outliers-removal Disable corner outlier filtering --no-final-filtering Disable filtering after all views have been processed. --min-views-outlier MINVIEWOUTLIER Number of raw views to initialize statistics (default: 20) --use-blakezisserman Enable the Blake-Zisserman m-estimator --plot-outliers Plot the detect outliers during extraction (this could be slow) Output options: --verbose Enable (really) verbose output (disables plots) --show-extraction Show the calibration target extraction. (disables plots) --plot Plot during calibration (this could be slow). --dont-show-report Do not show the report on screen after calibration. Output the following three files after finish calibration: * ``camchain-homezhangsbagstatic_10hz.yaml`` * ``report-cam-homezhangsbagstatic_10hz.pdf`` * ``results-cam-homezhangsbagstatic_10hz.txt`` .. tip:: If you use camera parameters in Vins,it would be better to choose the pinhole-equi model or the omni-radtan model.If you use camera parameters in Maplab,please choose pinhole-equi model Calibrate the pose relationship between camera and IMU coordinate system ------------------------------------------------------------------------- * **Collect calibration data**：as calibrate the pose relationship of camera,Kalibr supports two ways to collect data,we still use ``rosbag`` here. * Method of collecting image: fix ``apilgrid`` calibration board, move camera * Make sure that the data collected is good:the brightness of the calibration board should be appropriate,too bright or too dark can't guarantee the quality of data,meanwhile do not shake too fast to avoid blurring of the image. * Set the imu publishing frequency to 200Hz,image to 20Hz(recommended by kalibr) * Fully motivate each axis of the imu,for example ,3 actions on each axis,then in the \"8-shaped\" motion * Record camera and imu as ``dynamic.bag``. .. code-block:: bash $ roslaunch mynt_eye_ros_wrapper display.launch $ cd bag $ rosbag record -O dynamic /mynteye/left/image_raw /mynteye/right/image_raw /mynteye/imu/data_raw #remember set image hz to 20hz, imu hz to 200hz * kalibr calibration: .. code-block:: bash $ kalibr_calibrate_imu_camera --cam camchain-homezhangsbagstatic_10hz.yaml --target aprilgrid.yaml --imu imu.yaml --time-calibration　--bag ~/bag/dynamic.bag View the parameters' meanings by kalibr_calibrate_imu_camera command .. code-block:: bash $ kalibr_calibrate_imu_camera --h Calibrate the spatial and temporal parameters of an IMU to a camera chain. usage: Example usage to calibrate a camera system against an IMU using an aprilgrid with temporal calibration enabled. kalibr_calibrate_imu_camera --bag MYROSBAG.bag --cam camchain.yaml --imu imu.yaml \ --target aprilgrid.yaml --time-calibration camchain.yaml: is the camera-system calibration output of the multiple-camera calibratin tool (kalibr_calibrate_cameras) example aprilgrid.yaml: | example imu.yaml: (ADIS16448) target_type: 'aprilgrid' | accelerometer_noise_density: 0.006 tagCols: 6 | accelerometer_random_walk: 0.0002 tagRows: 6 | gyroscope_noise_density: 0.0004 tagSize: 0.088 | gyroscope_random_walk: 4.0e-06 tagSpacing: 0.3 | update_rate: 200.0 optional arguments: -h, --help show this help message and exit Dataset source: --bag BAGFILE Ros bag file containing image and imu data (rostopics specified in the yamls) --bag-from-to bag_from_to bag_from_to Use the bag data starting from up to this time [s] --perform-synchronization Perform a clock synchronization according to 'Clock synchronization algorithms for network measurements' by Zhang et al. (2002). Camera system configuration: --cams CHAIN_YAML Camera system configuration as yaml file --recompute-camera-chain-extrinsics Recompute the camera chain extrinsics. This option is exclusively recommended for debugging purposes in order to identify problems with the camera chain extrinsics. --reprojection-sigma REPROJECTION_SIGMA Standard deviation of the distribution of reprojected corner points [px]. (default: 1.0) IMU configuration: --imu IMU_YAMLS [IMU_YAMLS ...] Yaml files holding the IMU noise parameters. The first IMU will be the reference IMU. --imu-delay-by-correlation Estimate the delay between multiple IMUs by correlation. By default, no temporal calibration between IMUs will be performed. --imu-models IMU_MODELS [IMU_MODELS ...] The IMU models to estimate. Currently supported are 'calibrated', 'scale-misalignment' and 'scale- misalignment-size-effect'. Calibration target: --target TARGET_YAML Calibration target configuration as yaml file Optimization options: --time-calibration Enable the temporal calibration --max-iter MAX_ITER Max. iterations (default: 30) --recover-covariance Recover the covariance of the design variables. --timeoffset-padding TIMEOFFSET_PADDING Maximum range in which the timeoffset may change during estimation [s] (default: 0.01) Output options: --show-extraction Show the calibration target extraction. (disables plots) --extraction-stepping Show each image during calibration target extraction (disables plots) --verbose Verbose output (disables plots) --dont-show-report Do not show the report on screen after calibration. Output the follwing 4 files after finish calibration: * ``camchain-imucam-homezhangsbagdynamic.yaml`` * ``imu-homezhangsbagdynamatic.yaml`` * ``report-imucam-homezhangsbagdynamic.pdf`` * ``results-imucam-homezhangsbagdynamic.yaml``