ROS：ubuntu-Ros使用OrbSLAM

一般无误的官方连接：https://github.com/raulmur/ORB_SLAM

ubuntu16.04没有多少改变，还是使用kinetic老代替indigo

Related Publications:

Artical:

[1] Raúl Mur-Artal, J. M. M. Montiel and Juan D. Tardós. ORB-SLAM: A Versatile and Accurate Monocular SLAM System.IEEE Transactions on Robotics, vol. 31, no. 5, pp. 1147-1163, 2015.

DOI: 10.1109/TRO.2015.2463671.

Link to pdf: http://webdiis.unizar.es/~raulmur/MurMontielTardosTRO15.pdf

1. License

ORB-SLAM is released under a GPLv3 license. Please note that we provide along ORB-SLAM a modified version of g2o and DBoW2 which are both BSD.

For a closed-source version of ORB-SLAM for commercial purposes, please contact the authors.

If you use ORB-SLAM in an academic work, please cite:

@article{murAcceptedTRO2015,
  title={{ORB-SLAM}: a Versatile and Accurate Monocular {SLAM} System},
  author={Mur-Artal, Ra\'ul, Montiel, J. M. M. and Tard\'os, Juan D.},
  journal={IEEE Transactions on Robotics},
  volume={31},
  number={5},
  pages={1147--1163},
  doi = {10.1109/TRO.2015.2463671},
  year={2015}
 }

2. Prerequisites (dependencies)

2.1 Boost

   We use the Boost library to launch the different threads of our SLAM system.

 sudo apt-get install libboost-all-dev 

2.2 ROS

      We use ROS to receive images from the camera or from a recorded sequence (rosbag), and for visualization (rviz, image_view).We have tested ORB-SLAM in Ubuntu 12.04 with ROS Fuerte, Groovy and Hydro; and in Ubuntu 14.04 with ROS Indigo. If you do not have already installed ROS in your computer, we recommend you to install the Full-Desktop version of ROS Fuerte (http://wiki.ros.org/fuerte/Installation/Ubuntu).

If you use ROS Indigo, remove the depency of opencv2 in the manifest.xml.

2.3 g2o (included)

       We use g2o to perform several optimizations. We include a modified copy of the library including only the components we need and also some changes that are listed inThirdparty/g2o/Changes.txt. In order to compile g2o you will need to have installed CHOLMOD, BLAS, LAPACK and Eigen3.

sudo apt-get install libsuitesparse-dev
sudo apt-get install libblas-dev
sudo apt-get install liblapack-dev
sudo apt-get install libeigen3-dev

2.4 DBoW2 (included)

        We make use of some components of the DBoW2 library (https://github.com/dorian3d/DBoW2) for place recognition and feature matching. We include a modified copy of the library including only the components we need and also some modifications that are listed inThirdparty/DBoW2/LICENSE.txt. It only depends on OpenCV, but it should be included in the ROS distribution.

3. Installation

1. Make sure you have installed ROS and all library dependencies (boost, eigen3, cholmod, blas, lapack).

2. Clone the repository:

3. git clone https://github.com/raulmur/ORB_SLAM.git ORB_SLAM

1. Add the path where you cloned ORB-SLAM to the ROS_PACKAGE_PATH environment variable (better if you add the export line to your .bashrc file)

2. Build g2o. Go into Thirdparty/g2o/ and execute:

3. mkdir build
   cd build
   cmake .. -DCMAKE_BUILD_TYPE=Release
   make 

   
   

4. Tip: To achieve the best performance in your computer, set your favorite compilation flags in line 97 and 98 ofThirdparty/g2o/CMakeLists.txt (by default -03 -march=native)

5. Build DBoW2. Go into Thirdparty/DBoW2/ and execute:

6. mkdir build
   cd build
   cmake .. -DCMAKE_BUILD_TYPE=Release
   make (如果未安装OpenCV，首先编译OpenCV：
   ubuntu16.04下编译安装OpenCV ) 
   

   
   

7. Tip: Set your favorite compilation flags in line 4 and 5 of Thirdparty/DBoW2/CMakeLists.txt (by default -03 -march=native)

8. Build ORB_SLAM. In the ORB_SLAM root execute:

                 If you use ROS Indigo, remove the depency of opencv2 in the manifest.xml.

9. mkdir build
   cd build
   cmake .. -DROS_BUILD_TYPE=Release
   make

   
   

10. Tip: Set your favorite compilation flags in line 12 and 13 of ./CMakeLists.txt (by default -03 -march=native)

             出现问题：

                    cmake .. -DROS_BUILD_TYPE=Release

           1.        这一句出现：

                           CMake Error at CMakeLists.txt:2 (include):
                           include could not find load file: 

                             /core/rosbuild/rosbuild.cmake


                         CMake Error at CMakeLists.txt:4 (rosbuild_init):
                          Unknown CMake command "rosbuild_init".


                         -- Configuring incomplete, errors occurred!
                        See also "/home/wishchin/WorkFrameSrc/ORB_SLAM-master/build/CMakeFiles/CMakeO

 

                解决方法：原因是ROS path 没有自动添加，需要进行手动添加。

         shell语句：

source /opt/ros/indigo/setup.bash   source /opt/ros/kinetic/setup.bash 

切换到主目录下。。。。
source  .bashrc #使能

       2.    出现：                     

[rosbuild] Building package ORB_SLAM-master
[rosbuild] Error from directory check: /opt/ros/indigo/share/ros/core/rosbuild/bin/check_same_directories.py  /home/wishchin/WorkFrameSrc/ORB_SLAM-master
1
Traceback (most recent call last):
  File "/opt/ros/indigo/share/ros/core/rosbuild/bin/check_same_directories.py", line 46, in <module>
    raise Exception
Exception
CMake Error at /opt/ros/indigo/share/ros/core/rosbuild/private.cmake:102 (message):
  [rosbuild] rospack found package "ORB_SLAM-master" at "", but the current
  directory is "/home/wishchin/WorkFrameSrc/ORB_SLAM-master".  You should
  double-check your ROS_PACKAGE_PATH to ensure that packages are found in the
  correct precedence order.
Call Stack (most recent call first):
  /opt/ros/indigo/share/ros/core/rosbuild/public.cmake:177 (_rosbuild_check_package_location)
  CMakeLists.txt:4 (rosbuild_init)


-- Configuring incomplete, errors occurred!
See also "/home/wishchin/WorkFrameSrc/ORB_SLAM-master/build/CMakeFiles/CMakeOutput.log".

         解决方法：                      

         在.bashrc 末尾添加：export  ROS_PACKAGE_PATH=$ROS_PACKAGE_PATH:/home/wishchin/WorkFrameSrc/ORB_SLAM

         ORB路径添加到ROS

             

7.编译成功：

[ 11%] Building CXX object CMakeFiles/ORB_SLAM-master.dir/src/Tracking.cc.o
[ 16%] Building CXX object CMakeFiles/ORB_SLAM-master.dir/src/LocalMapping.cc.o
[ 22%] Building CXX object CMakeFiles/ORB_SLAM-master.dir/src/LoopClosing.cc.o
[ 27%] Building CXX object CMakeFiles/ORB_SLAM-master.dir/src/ORBextractor.cc.o
[ 33%] Building CXX object CMakeFiles/ORB_SLAM-master.dir/src/ORBmatcher.cc.o
[ 38%] Building CXX object CMakeFiles/ORB_SLAM-master.dir/src/FramePublisher.cc.o
[ 44%] Building CXX object CMakeFiles/ORB_SLAM-master.dir/src/Converter.cc.o
[ 50%] Building CXX object CMakeFiles/ORB_SLAM-master.dir/src/MapPoint.cc.o
[ 55%] Building CXX object CMakeFiles/ORB_SLAM-master.dir/src/KeyFra

4. Usage

See section 5 to run the Example Sequence.

1. Launch ORB-SLAM from the terminal (roscore should have been already executed):

   rosrun ORB_SLAM ORB_SLAM PATH_TO_VOCABULARY PATH_TO_SETTINGS_FILE
   

   You have to provide the path to the ORB vocabulary and to the settings file. The paths must be absolute or relative to the ORB_SLAM directory.
   We already provide the vocabulary file we use in ORB_SLAM/Data/ORBvoc.txt.tar.gz. Uncompress the file, as it will be loaded much faster.

2. The last processed frame is published to the topic /ORB_SLAM/Frame. You can visualize it usingimage_view:

   rosrun image_view image_view image:=/ORB_SLAM/Frame _autosize:=true
   

3. The map is published to the topic /ORB_SLAM/Map, the current camera pose and global world coordinate origin are sent through/tf in frames/ORB_SLAM/Camera and/ORB_SLAM/World respectively. Runrviz to visualize the map:

   in ROS Fuerte:

   rosrun rviz rviz -d Data/rviz.vcg
   

   in ROS Groovy or a newer version:

   rosrun rviz rviz -d Data/rviz.rviz
   

4. ORB_SLAM will receive the images from the topic /camera/image_raw. You can now play your rosbag or start your camera node. If you have a sequence with individual image files, you will need to generate a bag from them. We provide a tool to do that: https://github.com/raulmur/BagFromImages.

Tip: Use a roslaunch to launch ORB_SLAM, image_view andrviz from just one instruction. We provide an example:

in ROS Fuerte:

roslaunch ExampleFuerte.launch

in ROS Groovy or a newer version:

roslaunch ExampleGroovyOrNewer.launch

5. Example Sequence

We provide the settings and the rosbag of an example sequence in our lab. In this sequence you will see a loop closure and two relocalisation from a big viewpoint change.

1. Download the rosbag file:
   http://webdiis.unizar.es/~raulmur/orbslam/downloads/Example.bag.tar.gz.

   Alternative link: https://drive.google.com/file/d/0B8Qa2__-sGYgRmozQ21oRHhUZWM/view?usp=sharing

   Uncompress the file.

2. Launch ORB_SLAM with the settings for the example sequence. You should have already uncompressed the vocabulary file (/Data/ORBvoc.txt.tar.gz)

   in ROS Fuerte:

   roslaunch ExampleFuerte.launch
   

   in ROS Groovy or newer versions:

   rosbag play --pause Example.bag  +空格键

   roslaunch ExampleGroovyOrNewer.launch

3. Once the ORB vocabulary has been loaded, play the rosbag (press space to start):

   rosbag play --pause Example.bag
   

6. The Settings File

ORB_SLAM reads the camera calibration and setting parameters from a YAML file. We provide an example inData/Settings.yaml, where you will find all parameters and their description. We use the camera calibration model of OpenCV.

Please make sure you write and call your own settings file for your camera (copy the example file and modify the calibration)

7. Failure Modes

You should expect to achieve good results in sequences similar to those in which we show results in our paper [1], in terms of camera movement and texture in the environment. In general our Monocular SLAM solution is expected to have a bad time in the following situations:

• Pure rotations in exploration
• Low texture environments
• Many (or big) moving objects, especially if they move slowly.

The system is able to initialize from planar and non-planar scenes. In the case of planar scenes, depending on the camera movement relative to the plane, it is possible that the system refuses to initialize, see the paper [1] for details.

8. Need Help?

If you have any trouble installing or running ORB-SLAM, contact the authors.