rgbdslam_v2_2kinect:RGBD-SLAM 校准 kinect 姿态，并在少数特征环境中猛击

# RGBDSLAM<i>v2</i> ```beta version``` ... is a state-of-the-art SLAM system for RGB-D cameras, e.g., the Microsoft Kinect. You can use it to create highly accurate 3D point clouds or OctoMaps. RGBDSLAMv2 is based on the ROS project, OpenCV, PCL, OctoMap, SiftGPU and more - thanks! A journal article with a system description and performance evaluation can be found in the following publication: "3D Mapping with an RGB-D Camera",<br/> *F. Endres, J. Hess, J. Sturm, D. Cremers, W. Burgard*,<br/> IEEE Transactions on Robotics, 2014. Additional information can be found here:<br/> * www.informatik.uni-freiburg.de/~endres * http://www.ros.org/wiki/rgbdslam * http://answers.ros.org/questions/tags:rgbdslam <img src="http://raw.githubusercontent.com/felixendres/rgbdslam_v2/hydro/media/rgbdslamv2_fr2desk.jpg" alt="RGBDSLAM on the RGB-D Benchmark Dataset" width="600"> # Prerequisites ################################################################ - Ubuntu 12.04 - 13.04 - [ROS hydro](http://wiki.ros.org/hydro/) - Problems may occur when using a version of the PCL library different from the ROS hydro version. # Installation ################################################################ The installation of RGBDSLAMv2 for ROS hydro should be straigh. A copy-pastable walkthrough can be found below 1. Put RGBDSLAMv2 in a catkin workspace: See [the catkin tutorial](http://wiki.ros.org/catkin/Tutorials/create_a_workspace) for details. Use git to clone this repository into your workspace's "src/" directory. Or download RGBDSLAMv2 as an [archive](http://codeload.github.com/felixendres/rgbdslam_v2/zip/hydro) and extract it to "src/". 3. Use rosdep (i.e. "rosdep install rgbdslam") to install missing dependencies. For details see http://wiki.ros.org/ROS/Tutorials/rosdep 4. To build RGBDSLAMv2 go to your catkine workspace and execute "catkin_make". If you get an error about the missing siftgpu library, execute "catkin_make" again. ##Installation from Scratch ##################################################### Assuming you have installed ROS hydro on Ubuntu, issue the following commands in a terminal (or copy-paste the whole sequence at once) #Prepare Workspace source /opt/ros/hydro/setup.bash mkdir -p ~/rgbdslam_catkin_ws/src cd ~/rgbdslam_catkin_ws/src catkin_init_workspace cd ~/rgbdslam_catkin_ws/ catkin_make source devel/setup.bash #Get RGBDSLAM cd ~/rgbdslam_catkin_ws/src wget -q http://github.com/felixendres/rgbdslam_v2/archive/hydro.zip unzip -q hydro.zip cd ~/rgbdslam_catkin_ws/ #Install rosdep update rosdep install rgbdslam catkin_make catkin_make # Installation done! What's next? See the sections below for more details on the usage. But to get you started quickly here's the most important pointers: - If you want to use RGBDSLAMv2 with an RGB-D camera you may have to install openni (sudo apt-get install ros-hydro-openni-launch). - Check out the launch files in "launch/" for examples and specific use cases. roslaunch rgbdslam openni+rgbdslam.launch is a good starting point for live mapping. - Check out the README in "test/" for running, testing and evaluating RGBDSLAMv2 on Juergen Sturm's RGB-D SLAM Dataset and Benchmark: http://vision.in.tum.de/data/datasets/rgbd-dataset <img src="http://raw.githubusercontent.com/felixendres/rgbdslam_v2/hydro/media/rgbdslamv2_empty.jpg" alt="RGBDSLAM right after startup" width="600"> ## IMPORTANT NOTE ################################################################ This software is an update of the ROS Fuerte version of RGBDSLAM. However many things have changed, so some of the DOCUMENTATION BELOW MAY BE OUTDATED. Please report problems with the documentation. Thanks. # Configuration ############################################################## There are several example launch-files that set the parameters of RGB-D SLAM for certain use cases. For a definitive list of all settings and their default settings have a look at their quite readable definition in src/parameter_server.cpp or (with the current settings instead of the default) in the GUI Menu Settings->View Current Settings. The various use-case launch-files might not work correctly yet, as they are not regularly tested. You should get them running if you fiddle with the topics ("rostopic list" and "rosnode info" will help you. "rqt_graph" is great too). # Usage ############################################################## Most people seem to want the registered point cloud. It is by default sent out on /rgbdslam/batch_clouds when you command RGB-D SLAM to do so (see below). The clouds sent are actually the same as before, but the according transformation - by default from /map to /openni_camera - is sent out on /tf. The octoMap library is compiled into the rgbdslam node. This allows to create the octomap directly. In the GUI this can be done by selecting "Save Octomap" from the "Data" Menu. Online octomapping is possible, but not recommended. <img src="http://raw.githubusercontent.com/felixendres/rgbdslam_v2/hydro/media/rgbdslamv2_fr2desk_octomap.jpg" width="600" alt="OctoMap created from the RGB-D Benchmark sequence fr2/desk"> ## Usage with GUI ################################################################# To start RGBDSLAMv2 launch, e.g., $ roslaunch rgbdslam openni+rgbdslam.launch Alternatively you can start the openni nodes and RGBDSLAMv2 separately, e.g.: roslaunch openni_camera openni_node.launch roslaunch rgbdslam rgbdslam.launch To capture models either press space to start recording a continuous stream or press enter to record a single frame. To reduce data redundancy, sequential frames from (almost) the same position are not included in the final model. Parameters RGBDSLAMv2 is customizable by parameters. These should be set in the launch file. Parameters can be changed during operation from the GUI, however, changes from the GUI may have no effect for many parameters. Visualization The 3D visualization shows the globally optimized model (you might have to click into it to update the view after optimization). Neighbouring points can be triangulated except at missing values and depth jumps. With the shortcut "t", triangulation can be toggled. Since raw points render slightly faster the parameter "cloud_display_type" controls whether triangulation is computed at all - at the time the cloud is received. The parameter "gl_point_size" may be useful to most users. ## Usage without GUI ############################################################## The RosUI is an alternative to the Grapical_UI to run the rgbdslam headless, for example on the PR2. rgbdslam can then be used via service-calls. The possible calls are: * /rgbdslam/ros_ui {reset, quick_save, send_all, delete_frame, optimize, reload_config, save_trajectory} * /rgbdslam/ros_ui_b {pause, record} {true, false} * /rgbdslam/ros_ui_f {set_max} {float} * /rgbdslam/ros_ui_s {save_octomap, save_cloud, save_g2o_graph, save_trajectory, save_features, save_individual} {filename} To start the rgbdslam headless use the headless.launch: $ roslaunch rgbdslam headless.launch Capture single frames via: $ rosservice call /rgbdslam/ros_ui frame Capture a stream of data: $ rosservice call /rgbdslam/ros_ui_b pause false Send point clouds with computed transformations (e.g., to rviz or octomap_server): $ rosservice call /rgbdslam/ros_ui send_all Save data using one of the following: All pointclouds in one file quicksave.pcd in rgbdslam/bin-directory: $ rosservice call /rgbdslam/ros_ui_s save_cloud Every pointcloud in its own file in rgbdslam/bin-directory: $ rosservice call /rgbdslam/ros_ui save_individual /rgbdslam/ros_ui: * reset ''resets the graph, delets all nodes (refreshes only when capturing new images)'' * frame ''capture one frame from the sensor'' * optimize ''trigger graph optimizer'' * reload_config ''reloads the paramters from the ROS paramter server'' * quick_save ''sav