Hanjie's Blog

一只有理想的羊驼

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首先需要在GitHub上下载Hexo的源代码，然后安装：

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hexo init
npm install hexo
npm install -g

安装调试程序：

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npm install -g node-inspector

输入 node-inspector 启动调试工具，然后1：

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node --debug-brk=5858 node_modules/.bin/hexo generate

调试工具会监听5858端口。然后打开一个新的终端，输入2：

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node-inspector

打开Chrome输入http://127.0.0.1:8080/?ws=127.0.0.1:8080&port=5858，脚本现在就已经断点在了第一行3。

  1. http://stackoverflow.com/questions/30942953/how-can-i-debug-a-node-app-that-is-started-via-the-command-line-cli-like-forev↩︎

  2. http://blog.domlib.com/articles/686.html↩︎

  3. http://xzper.com/2014/08/17/浅析Hexo的Generate命令/↩︎

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系统配置1

系统内核
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uname -r

内核必须要至少3.5.0版本。

Dependences
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# Ubuntu 16.04
sudo apt-get install libraw1394-11 libgtkmm-2.4-1v5 libglademm-2.4-1v5 libgtkglextmm-x11-1.2-dev libgtkglextmm-x11-1.2 libusb-1.0-0

# Ubuntu 14.04
sudo apt-get install libraw1394-11 libgtkmm-2.4-1v5 libglademm-2.4-1v5 libgtkglextmm-x11-1.2-dev libgtkglextmm-x11-1.2 libusb-1.0-0

# Ubuntu 12.04
sudo apt-get install libgtkmm-2.4-dev libglademm-2.4-dev libusb-1.0-0
系统设置
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sudo gedit /etc/default/grub

将

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GRUB_CMDLINE_LINUX_DEFAULT="quiet splash"

替换为

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GRUB_CMDLINE_LINUX_DEFAULT="quiet splash usbcore.usbfs_memory_mb=1000"

保存后执行：

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sudo update-grub

重启，然后运行下指令测试：

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cat /sys/module/usbcore/parameters/usbfs_memory_mb

安装FlyCapture SDK

For 14.04: 

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cd tools/flycapture2-2.9.3.43-amd64

sudo apt-get install libraw1394-11 libgtkmm-2.4-1c2a libglademm-2.4-1c2a libgtkglextmm-x11-1.2-dev libgtkglextmm-x11-1.2 libusb-1.0-0 libglademm-2.4-dev

sudo sh install_flycapture.sh

For 16.04: 

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cd tools/flycapture2-2.11.3.164-amd64

sudo apt-get install libraw1394-11 libavcodec-ffmpeg56               \
        libavformat-ffmpeg56 libswscale-ffmpeg3 libswresample-ffmpeg1        \
		libavutil-ffmpeg54 libgtkmm-2.4-dev libglademm-2.4-dev               \
		libgtkglextmm-x11-1.2-dev libusb-1.0-0
		
sudo sh install_flycapture.sh

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Would you like to add a udev entry to allow access to IEEE-1394 and USB hardware?
If this is not ran then your cameras may be only accessible by running flycap as sudo.
(y/n)$ y
Launching conf script

This script will assist users in configuring their udev rules to allow
access to 1394 and USB devices. The script will create a udev rule which
will add the 1394 cards and USB devices to a group called pgrimaging.
The user may also choose to restart the udev daemon. All of this can be done
manually as well.  Please note that this script will change the permissions
for all IEEE1394 devices including hard drives and web cams. It will allow
the user to read and modify data on any IEEE1394 device.


Enter the name of the user to add to this user group.
$ yourusername
Is this user name ok?: yourusername
(y/n)$ y

Add user yourusername to group pgrimaging.
Is this ok?:
(y/n)$ y

Writing the udev rules file.

Do you want to restart the udev daemon?
(y/n)$ y
udev stop/waiting
udev start/running, process 5764

Configuration complete. A reboot may be required on some systems for changes to take effect

Complete

运行测试

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flycap
flycap

  1. https://www.ptgrey.com/tan/10685↩︎

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Hardware1

Firmware: v1.8

IMU has 3-axis accelerometer and 3-axis gyroscope to detect linear acceleration and rotational rate. IMU sampling rate is 250 Hz.

IMU Rotation and Translation

IMU Rotation matrix (Right-handed coordinate system, RUB (right-up-back), rotate 90° around the z-axis):

\[\left[ {\matrix{ 0&{ - 1}&0 \cr 1&0&0 \cr 0&0&1 } } \right]\]

Translation vector from camera to IMU (in meter):

Translation
Camera Left [ 0.07608, -0.00312, -0.01464]
Camera Right [-0.04392, -0.00312, -0.01464]

The value of z-axis is from the center of the lens to the board. The deviation maybe ±0.25mm because of the difference in focal length.

IMU Noise Density and Random Walk

Noise Density Random Walk
Accelerometer 7.6509e-02 5.3271e-02
Gyroscope 9.0086e-03 5.5379e-05

Install Opencv 3.4

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mkdir build
cd build
cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_TBB=ON -D BUILD_EXAMPLES=OFF -D BUILD_DOCS=OFF -D BUILD_PERF_TESTS=OFF -D BUILD_TESTS=OFF -D WITH_GTK_2_X=ON ..
make -j8
sudo make install

sudo /bin/bash -c 'echo "/usr/local/lib" > /etc/ld.so.conf.d/opencv.conf'
sudo ldconfig

Install MYNT-EYE-OKVIS-Sample2

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sudo apt-get install cmake libgoogle-glog-dev libatlas-base-dev libeigen3-dev libsuitesparse-dev libboost-dev libboost-filesystem-dev

git clone https://github.com/ethz-asl/okvis.git

mkdir build && cd build
cmake -DCMAKE_BUILD_TYPE=Release ..
make -j8
make install

Build Kalibr with catkin3

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cd ~/catkin_ws/src
git clone https://github.com/ethz-asl/Kalibr.git
cd ..
catkin_make -DCMAKE_BUILD_TYPE="Release" -j4
source ./devel/setup.sh

Calibrate Camera and IMU

Steps4
  1. Calibration targets

You can download from the website or created by yourself followed the instructions5

  1. Get dataset of stereo camera and IMU.

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cd mynt-eye-okvis-sample/build
./okvis_app_getcameraimucalibdataset 0 ./cameraimu/cam0/ ./cameraimu/cam1/ ./cameraimu/imu0.csv
0 means that it use video1, ./cameraimu/cam0 is the folder to store left images, ./camera/cam0 is the folder to store right images, ./cameraimu/imu0.csv is the file to store the data of imu.

  1. Use kalibrbagcreate creat calibration bag of stereo camera and imu. First move the folder of camera to kalibr's workspace, then creat calibration bag.

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cd ~/catkin_ws/
source ./devel/setup.sh
kalibr_bagcreater --folder cameraimu/. --output-bag cameraimucalib.bag

  1. Calibrate stereo camera

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kalibr_calibrate_cameras --target april_5x8.yaml cameraimucalib.bag --models pinhole-radtan pinhole-radtan --topics /cam0/image_raw /cam1/image_raw

april_5x8.yaml is the config file of calibration target which looks like:

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target_type: 'aprilgrid' #gridtype
tagCols: 5               #number of apriltags
tagRows: 8               #number of apriltags
tagSize: 0.025           #size of apriltag, edge to edge [m]
tagSpacing: 0.3          #ratio of space between tags to tagSize

The file will looks like if using checkerboard:

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targetType: 'checkerboard' #gridtype
targetCols: 6              #number of internal chessboard corners
targetRows: 7              #number of internal chessboard corners
rowsMetricSize: 0.06       #size of one chessboard square [m]
colsMetricSize: 0.06       #size of one chessboard square [m]

  1. Camera stereo camera and imu

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kalibr_calibrate_imu_camera --target april_5x8.yaml --cam cameracalib.yaml --imu imu.yaml --bag cameraimucalib.bag --bag-from-to 0 72

cameracalib.yaml is the config file of stereo camera generated by step 4, imu.yaml is config file of imu in mynt-eye-okvis-sample/config, from-to 0 72 means that it use bag from 0s to 72s to calibration.

Results

The Yaml formats of the calibration file can been seen from here.

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Calibration results
===================
Normalized Residuals
----------------------------
Reprojection error (cam0):     mean 0.246874712924, median 0.217537207629, std: 0.25184628687
Reprojection error (cam1):     mean 0.195955751013, median 0.175831842512, std: 0.140312508567
Gyroscope error (imu0):        mean 0.174678800713, median 0.142828483069, std: 0.187200875016
Accelerometer error (imu0):    mean 0.132150523822, median 0.108954584935, std: 0.106560662224

Residuals
----------------------------
Reprojection error (cam0) [px]:     mean 0.246874712924, median 0.217537207629, std: 0.25184628687
Reprojection error (cam1) [px]:     mean 0.195955751013, median 0.175831842512, std: 0.140312508567
Gyroscope error (imu0) [rad/s]:     mean 0.000282774195232, median 0.000231214143852, std: 0.000303045226801
Accelerometer error (imu0) [m/s^2]: mean 0.00348953062143, median 0.00287702499756, std: 0.00281381172859

Transformation (cam0):
-----------------------
T_ci:  (imu0 to cam0): 
[[ 0.04341751  0.99896022  0.01390713 -0.00252296]
 [-0.99902347  0.04329777  0.00879867  0.00163378]
 [ 0.00818737 -0.01427556  0.99986458 -0.0060169 ]
 [ 0.          0.          0.          1.        ]]

T_ic:  (cam0 to imu0): 
[[ 0.04341751 -0.99902347  0.00818737  0.00179099]
 [ 0.99896022  0.04329777 -0.01427556  0.0023637 ]
 [ 0.01390713  0.00879867  0.99986458  0.0060368 ]
 [ 0.          0.          0.          1.        ]]

timeshift cam0 to imu0: [s] (t_imu = t_cam + shift)
0.0


Transformation (cam1):
-----------------------
T_ci:  (imu0 to cam1): 
[[ 0.04587416  0.99870286  0.02209422 -0.12418407]
 [-0.99892623  0.04571856  0.00749699  0.00192461]
 [ 0.00647715 -0.02241441  0.99972778 -0.00529794]
 [ 0.          0.          0.          1.        ]]

T_ic:  (cam1 to imu0): 
[[ 0.04587416 -0.99892623  0.00647715  0.00765369]
 [ 0.99870286  0.04571856 -0.02241441  0.12381624]
 [ 0.02209422  0.00749699  0.99972778  0.00802582]
 [ 0.          0.          0.          1.        ]]

timeshift cam1 to imu0: [s] (t_imu = t_cam + shift)
0.0

Baselines:
----------
Baseline (cam0 to cam1): 
[[ 0.99996344 -0.00239335  0.00820977 -0.12160789]
 [ 0.00240439  0.99999622 -0.00133526  0.00028887]
 [-0.00820654  0.00135495  0.99996541  0.00069583]
 [ 0.          0.          0.          1.        ]]
baseline norm:  0.121610228073 [m]


Gravity vector in target coords: [m/s^2]
[ 7.91261884  0.21833681 -5.7888872 ]


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

cam0
-----
  Camera model: pinhole
  Focal length: [441.99817968009677, 441.66869887034943]
  Principal point: [369.9738561699648, 234.13190157824815]
  Distortion model: radtan
  Distortion coefficients: [-0.2974398881998292, 0.08194961900031578, 0.00022897719568841816, -0.00012227166858536044]
  Type: aprilgrid
  Tags: 
    Rows: 8
    Cols: 5
    Size: 0.025 [m]
    Spacing 0.0075 [m]


cam1
-----
  Camera model: pinhole
  Focal length: [441.6397246072589, 441.52814086273514]
  Principal point: [344.95454482822214, 263.0207032045381]
  Distortion model: radtan
  Distortion coefficients: [-0.3086004799815589, 0.0952146365061291, -0.00035306500466706703, 0.000399686074862005]
  Type: aprilgrid
  Tags: 
    Rows: 8
    Cols: 5
    Size: 0.025 [m]
    Spacing 0.0075 [m]



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

IMU0:
----------------------------
  Model: calibrated
  Update rate: 500
  Accelerometer:
    Noise density: 0.0011809 
    Noise density (discrete): 0.0264057267463 
    Random walk: 8.2583e-05
  Gyroscope:
    Noise density: 7.2396e-05
    Noise density (discrete): 0.00161882377299 
    Random walk: 1.3e-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]
cali
cali
cali
cali

  1. https://slightech.github.io/MYNT-EYE-SDK/index.html↩︎

  2. https://github.com/slightech/MYNT-EYE-OKVIS-Sample↩︎

  3. https://github.com/ethz-asl/kalibr/wiki/installation↩︎

  4. https://github.com/slightech/MYNT-EYE-OKVIS-Sample/blob/mynteye/cameraimu_calibration_guidebook.md↩︎

  5. https://github.com/ethz-asl/kalibr/wiki/calibration-targets↩︎

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