kalibr进行相机内参以及相机imu的融合标定
1、采集标定数据
参考该视频教程：
https://www.youtube.com/watch?app=desktop&v=puNXsnrYWTY
2、转rosbag包
首先安装好Docker
在linux下运行如下命令，获取 VideoIMUCapture-Android 的github库
git clone https://github.com/DavidGillsjo/VideoIMUCapture-Android.git进入对应文件夹
cd VideoIMUCapture-Android/calibration需要以root权限进入容器，那么需要输入类似命令，换为自己的路径
SUDO=1 DUSER=root DATA=/home/ljy18/VideoIMUCapture-Android/dataset ./run_dockerhub.sh容器是退出后删除，文件夹挂在到容器内后对应的目录为/data
需要转为euroc格式的数据集bag包，原始文件夹格式需要为
dataset_name/
├── mav0/
│ ├── cam0/
│ │ ├── data/
│ │ │ ├── 1403....png
│ │ │ └── ...
│ │ ├── data.csv
│ ├── imu0/
│ │ ├── data.csv
其中：
mav0/cam0/data.csv的格式为
#timestamp [ns],filename
1403636579763555584,1403636579763555584.png
1403636579863555584,1403636579863555584.png
...
mav0/imu0/data.csv的格式为
#timestamp [ns],w_RS_S_x [rad s^-1],w_RS_S_y [rad s^-1],w_RS_S_z [rad s^-1],
a_RS_S_x [m s^-2],a_RS_S_y [m s^-2],a_RS_S_z [m s^-2]
1403636579763555584,-0.0015,0.0023,0.0009,9.8085,-0.0321,0.0230
...
Imu频率要远大于图片帧频率
用当前目录下的kalibr_bagcreater.py（见附录）去替换掉原本针对旧数据集格式的kalibr_bagcreater：
cp /data/kalibr_bagcreater.py /kalibr_workspace/src/Kalibr/aslam_offline_calibration/kalibr/python/kalibr_bagcreater转为bag包
kalibr_bagcreater \--folder /data/VideoTV00001_EuRoC \--output-bag /data/VideoTV00001_calibration/VideoTV00001_euroc.bag查看话题名称是否正确
rosbag info /data/VideoTV00001_calibration/VideoTV00001_euroc.bag出现类似如下内容即格式正确
types: sensor_msgs/Image [060021388200f6f0f447d0fcd9c64743]sensor_msgs/Imu [6a62c6daae103f4ff57a132d6f95cec2]topics: /cam0/image_raw 2154 msgs : sensor_msgs/Image/imu0 13542 msgs : sensor_msgs/Imu3、相机内参标定
进入标定文件夹
cd /data/VideoTV00001_calibration在该目录下新建一个target.yaml文件，这个是所用标定板的配置文件，参考标定板如图：
target.yaml文件内容为
tagCols: 6tagRows: 6tagSize: 0.021tagSpacing: 0.3target_type: aprilgrid其中tagSize是打印后每个格子的实际尺寸，单位是米。需要根据实际调整。
进行相机内参标定
kalibr_calibrate_cameras --bag VideoTV00001_euroc.bag --target target.yaml --models pinhole-radtan --topics /cam0/image_raw标定完成后会弹出可视化结果并输出标定结果文件至该目录下
4、相机imu外参标定
需要再新建imu.yaml和camchain.yaml文件
imu.yaml是imu内参的配置文件，可在产品手册中获取或者获取一小时以上imu的静置数据进行imu内参标定。Imu.yaml的格式如下：
accelerometer_noise_density: 0.00061667accelerometer_random_walk: 0.0000043333gyroscope_noise_density: 0.000098902gyroscope_random_walk: 0.0000012928rostopic: /imu0update_rate: 188.58097757972单位为
| gyroscope_noise_density | 角速度白噪声 | rad/s/√Hz |
| accelerometer_noise_density | 加速度白噪声 | m/s²/√Hz |
| gyroscope_random_walk | 陀螺仪偏置随机游走 | rad/s²/√Hz |
| accelerometer_random_walk | 加速度计偏置随机游走 | m/s³/√Hz |
update_rate根据实际频率填写
camchain.yaml是相机内参的配置文件，根据刚才相机内参的标定结果填写，camchain.yaml的内容格式如下：
cam0:cam_overlaps: []camera_model: pinholedistortion_coeffs: [0.07936144147573729, -0.09439727502429124, -0.001944215543450636,-0.0013778851088523114]distortion_model: radtanintrinsics: [643.3140528909328, 642.1840798849714, 986.8635102770212, 495.85841930165645]resolution: [1920, 1080]rostopic: /cam0/image_raw进行外参标定
kalibr_calibrate_imu_camera --target target.yaml --imu imu.yaml --cams camchain.yaml --bag VideoTV00001_euroc.bag标定完成后会弹出可视化结果并输出标定结果文件至该目录下
附录：新的kalibr_bagcreater.py内容如下，可以放在/data/目录下：
#!/usr/bin/env python# -*- coding: utf-8 -*-# Compatible with EuRoC dataset format# Structure:# dataset_name/# ├── mav0/# │ ├── cam0/# │ │ ├── data/# │ │ │ ├── 1403....png# │ │ │ └── ...# │ │ ├── data.csv# │ ├── imu0/# │ │ ├── data.csv## Output topics:# /cam0/image_raw# /imu0print("importing libraries...")import rosbagimport rospyfrom sensor_msgs.msg import Imagefrom sensor_msgs.msg import Imuimport ImageFileimport time, sys, osimport argparseimport cv2import numpy as npimport csvparser = argparse.ArgumentParser(description='Create a ROS bag using EuRoC dataset (images + IMU).')parser.add_argument('--folder', metavar='folder', required=True, help='Root folder of dataset (contains mav0)')parser.add_argument('--output-bag', metavar='output_bag', default="output.bag", help='ROS bag output path')parsed = parser.parse_args()# === Helper functions ===def read_image_list(cam_dir):"""Read image timestamps and filenames from camX/data.csv"""csv_path = os.path.join(cam_dir, "data.csv")data_dir = os.path.join(cam_dir, "data")images = []timestamps = []if not os.path.exists(csv_path):print(" Image CSV not found:", csv_path)return []with open(csv_path, 'r') as f:reader = csv.reader(f)header = next(reader, None)for row in reader:if len(row) < 2:continuets, filename = row[0], row[1]full_path = os.path.join(data_dir, filename)if os.path.exists(full_path):images.append((ts, full_path))else:print(" Missing image file:", full_path)# sort by timestampimages.sort(key=lambda x: int(x[0]))return imagesdef read_imu_data(imu_dir):"""Read IMU measurements from imu0/data.csv"""imu_csv = os.path.join(imu_dir, "data.csv")if not os.path.exists(imu_csv):print(" IMU CSV not found:", imu_csv)return []imu_data = []with open(imu_csv, 'r') as f:reader = csv.reader(f)header = next(reader, None)for row in reader:if len(row) < 7:continuetimestamp = row[0]gyro = [float(x) for x in row[1:4]]accel = [float(x) for x in row[4:7]]imu_data.append((timestamp, gyro, accel))return imu_datadef load_image_to_rosmsg(filename, timestamp_str):"""Convert image to ROS Image message with timestamp"""image_np = cv2.imread(filename, cv2.IMREAD_GRAYSCALE)if image_np is None:print(" Failed to load:", filename)return None, Nonesecs = int(timestamp_str[0:-9])nsecs = int(timestamp_str[-9:])timestamp = rospy.Time(secs, nsecs)rosimg = Image()rosimg.header.stamp = timestamprosimg.height = image_np.shape[0]rosimg.width = image_np.shape[1]rosimg.encoding = "mono8"rosimg.step = rosimg.widthrosimg.data = image_np.tostring()return rosimg, timestampdef create_imu_msg(timestamp_str, gyro, accel):"""Convert IMU sample to ROS Imu message"""secs = int(timestamp_str[0:-9])nsecs = int(timestamp_str[-9:])timestamp = rospy.Time(secs, nsecs)msg = Imu()msg.header.stamp = timestampmsg.angular_velocity.x = gyro[0]msg.angular_velocity.y = gyro[1]msg.angular_velocity.z = gyro[2]msg.linear_acceleration.x = accel[0]msg.linear_acceleration.y = accel[1]msg.linear_acceleration.z = accel[2]return msg, timestamp# === Main logic ===try:bag = rosbag.Bag(parsed.output_bag, 'w')print(" Creating bag:", parsed.output_bag)# Cameracam0_dir = os.path.join(parsed.folder, "mav0", "cam0")image_list = read_image_list(cam0_dir)print(" Found {} images".format(len(image_list)))for ts, filename in image_list:rosimg, t = load_image_to_rosmsg(filename, ts)if rosimg is not None:bag.write("/cam0/image_raw", rosimg, t)# IMUimu0_dir = os.path.join(parsed.folder, "mav0", "imu0")imu_list = read_imu_data(imu0_dir)print(" Found {} imu samples".format(len(imu_list)))for ts, gyro, accel in imu_list:imumsg, t = create_imu_msg(ts, gyro, accel)bag.write("/imu0", imumsg, t)print(" Finished writing bag file.")finally:bag.close()print(" Bag closed successfully.")