D435i标定摄像头和IMU笔记四（RGB摄像头和IMU联合标定篇）

 

D435i标定摄像头和IMU教程四（RGB摄像头和IMU联合标定篇）

• 一、前提
• 二、准备标定文件
  • 2.1 标定板yaml文件
  • 2.2 相机标定yaml文件
  • 2.3 imu标定yaml文件
  • 2.4 录制rosbag文件
  • 2.5 标定（运行时间很久很久）
  • 2.6 结果

 

参考视频
D435i标定摄像头和IMU笔记一（配置环境篇）
D435i标定摄像头和IMU笔记二（RGB摄像头标定篇）
D435i标定摄像头和IMU笔记二-2（RGB+双目多摄像头标定篇）
D435i标定摄像头和IMU笔记三（IMU标定篇)
D435i标定摄像头和IMU笔记四（RGB摄像头和IMU联合标定篇)
D435i标定摄像头和IMU笔记四-2（双目摄像头与IMU联合标定篇）

一、前提

我们已经对RGB摄像头和IMU进行了单独标定。Kalibr官方WIKI。

二、准备标定文件

2.1 标定板yaml文件

前面用到的checkerboard.yaml，可以直接使用。内容为：

target_type: 'checkerboard' #gridtype
targetCols: 5               #number of internal chessboard corners
targetRows: 8               #number of internal chessboard corners
rowSpacingMeters: 0.045      #size of one chessboard square [m]
colSpacingMeters: 0.045      #size of one chessboard square [m]

2.2 相机标定yaml文件

前面标定自动产生的camchain-camd435i.yaml，可以直接用。内容为：

cam0:
  cam_overlaps: []
  camera_model: pinhole
  distortion_coeffs: [0.16212545911017717, -0.24080691480176616, -0.004308195576417379,
    -0.0030299905015934016]
  distortion_model: radtan
  intrinsics: [611.3040953235151, 612.2272911356274, 313.980911449739, 237.49071739181224]
  resolution: [640, 480]
  rostopic: /color

2.3 imu标定yaml文件

需要根据IMU标定新建，参考D435i标定摄像头和IMU教程三（IMU标定篇）中的2.4。内容为：

rostopic: /imu
update_rate: 200.0 #Hz
 
gyroscope_noise_density: 3.0285738136227973e-03
gyroscope_random_walk: 3.0037305993425518e-05

accelerometer_noise_density: 2.7260051759783317e-02
accelerometer_random_walk: 5.7981798863344241e-04

2.4 录制rosbag文件

1. 启动D435i：Ctrl+Alt+t：终端1

roslaunch realsense2_camera rs_camera.launch 

1. rviz查看视野：Ctrl+Shift+t：终端2
2. 更改图像频率并转发为一个新话题：Ctrl+Shift+t：终端3

rosrun topic_tools throttle messages /camera/color/image_raw 20.0 /color

1. 更改IMU频率并转发为一个新话题：Ctrl+Shift+t：终端4

rosrun topic_tools throttle messages /camera/imu 200.0 /imu

1. 录制rosbag：Ctrl+Shift+t：终端5

rosbag record -O camer_imu /color /imu

PS：注意要对着标定板，确保能检测到角点，各个角度都录一下。三个轴，每个轴都来回三次。

2.5 标定（运行时间很久很久）

kalibr_calibrate_imu_camera --target checkerboard.yaml --cam camchain-camd435i.yaml --imu imu.yaml --bag camer_imu.bag

问题一：提示OverflowError: bad numeric conversion: positive overflow
解决办法：IMU数据获取有问题，我的是使用长线或者USB供电不足会出现这种问题。建议使用20cm左右的，好一点的或者原装数据线。

2.6 结果

生成了4个文件：

1. （相机校正结果）Saving camera chain calibration to file: camchain-imucam-camer_imu_2.yaml
2. （IMU校正结果）Saving imu calibration to file: imu-camer_imu_2.yaml
3. （详细数据）Detailed results written to file: results-imucam-camer_imu_2.txt
4. （联和标定报告）Report written to report-imucam-camer_imu_2.pdf
   展示详细数据：

Calibration results
===================
Normalized Residuals
----------------------------
Reprojection error (cam0):     mean 0.283157878598, median 0.21921505662, std: 0.252071973755
Gyroscope error (imu0):        mean 0.196325541059, median 0.0913923426892, std: 0.324390653502
Accelerometer error (imu0):    mean 0.189152781802, median 0.16916940251, std: 0.118189680733

Residuals
----------------------------
Reprojection error (cam0) [px]:     mean 0.283157878598, median 0.21921505662, std: 0.252071973755
Gyroscope error (imu0) [rad/s]:     mean 0.00840872140414, median 0.00391437988149, std: 0.0138938144099
Accelerometer error (imu0) [m/s^2]: mean 0.0729213007089, median 0.065217401265, std: 0.0455639360274

Transformation (cam0):
-----------------------
T_ci:  (imu0 to cam0): 
[[ 0.99943583  0.03338307 -0.0036876   0.02106939]
 [-0.03356636  0.9965747  -0.07557888  0.02139301]
 [ 0.00115191  0.07566002  0.99713301  0.03351284]
 [ 0.          0.          0.          1.        ]]

T_ic:  (cam0 to imu0): 
[[ 0.99943583 -0.03356636  0.00115191 -0.02037802]
 [ 0.03338307  0.9965747   0.07566002 -0.02455868]
 [-0.0036876  -0.07557888  0.99713301 -0.03172221]
 [ 0.          0.          0.          1.        ]]

timeshift cam0 to imu0: [s] (t_imu = t_cam + shift)
-0.00683194058101


Gravity vector in target coords: [m/s^2]
[-0.59332672  8.88845436 -4.10021528]


Calibration configuration
=========================

cam0
-----
  Camera model: pinhole
  Focal length: [611.3040953235151, 612.2272911356274]
  Principal point: [313.980911449739, 237.49071739181224]
  Distortion model: radtan
  Distortion coefficients: [0.16212545911017717, -0.24080691480176616, -0.004308195576417379, -0.0030299905015934016]
  Type: checkerboard
  Rows
    Count: 8
    Distance: 0.045 [m]
  Cols
    Count: 5
    Distance: 0.045 [m]



IMU configuration
=================

IMU0:
----------------------------
  Model: calibrated
  Update rate: 200.0
  Accelerometer:
    Noise density: 0.0272600517598 
    Noise density (discrete): 0.385515349097 
    Random walk: 0.000579817988633
  Gyroscope:
    Noise density: 0.00302857381362
    Noise density (discrete): 0.0428305016187 
    Random walk: 3.00373059934e-05
  T_i_b
    [[ 1.  0.  0.  0.]
     [ 0.  1.  0.  0.]
     [ 0.  0.  1.  0.]
     [ 0.  0.  0.  1.]]
  time offset with respect to IMU0: 0.0 [s]