ROS与VSLAM入门教程-RGBD-SLAM-V2安装

ROS与VSLAM入门教程-RGBD-SLAM-V2安装

说明：

• 介绍如何安装RGBD-SLAM-V2

环境：

• ubuntu16.04 + kinetic
• 深度相机：kinect v1

步骤：

• 通过脚本安装
• 下载脚本：

mkdir ~/RGBDSLAMV2
wget https://raw.githubusercontent.com/felixendres/rgbdslam_v2/kinetic/install.sh

• 修改目录为RGBDSLAMV2

vim install.sh

• 更改~/Code为~/RGBDSLAMV2
• 执行脚本

chmod +x  install.sh 
./install.sh 

安装kinect驱动:

• 安装驱动：

sudo apt-get install ros-kinetic-freenect-*

测试rgbdslam：

• 修改launch，设置启动驱动为freenect
• config/topic_image_depth深度话题修改为对应的

cd ~/RGBDSLAMV2/rgbdslam/launch
cp openni+rgbdslam.launch  freenect+rgbdslam.launch 
vim freenect+rgbdslam.launch 

• 修改后源码为：

<launch>
  <include file="$(find freenect_launch)/launch/freenect.launch"/>
  <node pkg="rgbdslam" type="rgbdslam" name="rgbdslam" cwd="node" required="true" output="screen"> 
    <!-- Input data settings-->
    <param name="config/topic_image_mono"              value="/camera/rgb/image_color"/> 
    <param name="config/topic_image_depth"             value="/camera/depth/image_raw"/>

    <!-- These are the default values of some important parameters -->
    <param name="config/feature_extractor_type"        value="ORB"/><!-- also available: SIFT, SIFTGPU, SURF, SURF128 (extended SURF), ORB. -->
    <param name="config/feature_detector_type"         value="ORB"/><!-- also available: SIFT, SURF, GFTT (good features to track), ORB. -->
    <param name="config/detector_grid_resolution"      value="3"/><!-- detect on a 3x3 grid (to spread ORB keypoints and parallelize SIFT and SURF) -->
    <param name="config/max_keypoints"                 value="600"/><!-- Extract no more than this many keypoints -->
    <param name="config/max_matches"                   value="300"/><!-- Keep the best n matches (important for ORB to set lower than max_keypoints) -->

    <param name="config/min_sampled_candidates"        value="4"/><!-- Frame-to-frame comparisons to random frames (big loop closures) -->
    <param name="config/predecessor_candidates"        value="4"/><!-- Frame-to-frame comparisons to sequential frames-->
    <param name="config/neighbor_candidates"           value="4"/><!-- Frame-to-frame comparisons to graph neighbor frames-->
    <param name="config/ransac_iterations"             value="100"/>
    <param name="config/cloud_creation_skip_step"      value="2"/><!-- subsample the images' pixels (in both, width and height), when creating the cloud (and therefore reduce memory consumption) -->

    
    <param name="config/cloud_display_type"            value="POINTS"/><!-- Show pointclouds as points (as opposed to TRIANGLE_STRIP) -->
    <param name="config/pose_relative_to"              value="largest_loop"/><!-- optimize only a subset of the graph: "largest_loop" = Everything from the earliest matched frame to the current one. Use "first" to optimize the full graph, "inaffected" to optimize only the frames that were matched (not those inbetween for loops) -->
    <param name="config/backend_solver"                value="pcg"/><!-- pcg is faster and good for continuous online optimization, cholmod and csparse are better for offline optimization (without good initial guess)-->
    <param name="config/optimizer_skip_step"           value="1"/><!-- optimize only every n-th frame -->

  </node>
</launch>

• 启动launch

roslaunch rgbdslam freenect+rgbdslam.launch

参考：

• https://github.com/felixendres/rgbdslam_v2
• http://felixendres.github.io/rgbdslam_v2/
• https://github.com/shl202/Turtlebot-Localization-Using-RGB-D-SLAM/wiki/Setup
• http://wiki.ros.org/rgbdslam
• http://sauravag.com/2016/10/how-to-setup-kinect-with-ros-and-rgbd-slam/
• http://www.cnblogs.com/voyagee/articles/6898278.html
• http://www.cnblogs.com/voyagee/p/7027076.html