Ubuntu 解決標楷體問題

安裝ubuntu14.04時, 如果選擇英語語系, 會幫你安裝中文套件, 預設字體是標楷體

解決方法;
   $ sudo vim /etc/fonts/conf.d/69-language-selector-zh-tw.conf

然後分別加入

<string>WenQuanYi Zen Hei</string>
<string>WenQuanYi Micro Hei</string>

<string>WenQuanYi Micro Hei Mono</string>

Dense Visual SLAM for RGB-D Cameras ( dvo_slam setups )

What is DVO SLAM

http://vision.in.tum.de/data/software/dvo

Requierements

Software: Ubuntu 12.04 using ROS Fuerte or Ubuntu 14.04 using ROS Indigo

Hardware: RGB-D cameras like RealSense r200, Asus Xtion, Kinect, etc.

(Optional)

If you use ubuntu 12.04 with ROS Fuerte and camera is Kinect or Xtion, you have to setup your camera first.

$ lsusb–v
$ sudo apt-get install ros-fuerte-openni-kinect

if it is 0601 not 0600(old verison)

$ sudo apt-get install --reinstall libopenni-sensor-primesense0
$ sudo gedit /etc/openni/GlobalDefaults.ini

Set `UsbInterface=2`

$ sudo reboot

After reboot, launch openni script, it will open your camera

$ roscore

$ roslaunch openni_launch openni.launch

Use image_view tool to see your RGB and depth images

$ rosrun image_view image_view image:=/camera/rgb/image_color

$ rosrun image_view image_view image:=/camera/depth/image

Clone the source

$ git clone https://github.com/jefftee/dvo_slam.git

$ rosmake dvo_core dvo_ros dvo_slam dvo_benchmark

Ubuntu 12.04 using ROS Fuerte:

$ git clone -b fuerte https://github.com/tum-vision/dvo_slam.git

or clone it from my repository (I add some launch files)

$ git clone -b fuerte git@bitbucket.org:TzuTaLin/dvo_slam.git

Build it

$ export ROS_PACKAGE_PATH=$ROS_PACKAGE_PATH:~/dvo_slam

$ sudo apt-get install ros-fuerte-libg2o liblapack-dev libblas-dev freeglut3-dev libqglviewer-qt4-dev libsuitesparse-dev libx11-dev

$ rosmake dvo_core dvo_ros dvo_slam dvo_benchmark

Clean

$ roscd your_package_name && make clean

Run keyframe tracker
$ rosrun dvo_slam camera_keyframe_tracker

Run tracker without keyframe
$ rosrun dvo_ros camera_tracker

Run and show configure, and Visualize

$ roslaunch dvo_slam qucikstart.lauch

Run benchmark
Download the dataset:
http://vision.in.tum.de/rgbd/dataset/freiburg1/rgbd_dataset_freiburg1_xyz.tgz

Extract it and go the folder

$ associate.py rgb.txt depth.txt > assoc.txt

You can download the tool from https://vision.in.tum.de/data/datasets/rgbd-dataset/tools

Than in the dataset folder,  run: 

$ roslaunch dvo_benchmark benchmark.launch keep_alive 
or
$ roslaunch dvo_benchmark benchmark.launch

Debug (Optional)

$ rosrun rqt rq

Change the name for registerd topics (Optional)

https://github.com/tum-vision/dvo_slam/blob/d25b65bff58860bb5a3a39a742459db3ba98eaa6/dvo_ros/src/camera_base.cpp

Dataset download

http://vision.in.tum.de/data/datasets/rgbd-dataset/download
http://alexteichman.com/octo/clams/

References:

http://www.alexteichman.com/octo/clams/
https://github.com/tum-vision/dvo_slam/issues/5
https://github.com/tum-vision/dvo_slam/issues/6
https://github.com/tum-vision/dvo_slam/issues/31
http://wiki.ros.org/rviz/Tutorials/Interactive%20Markers%3A%20Getting%20Started
http://blog.csdn.net/jasmine_shine/article/details/46444603

SLAM Tools:

http://vision.in.tum.de/data/datasets/rgbd-dataset/tools#evaluation
https://vision.in.tum.de/data/datasets/rgbd-dataset/tools