使用Kinect One（Kinect v2）运行RGBDSLAM总结

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在ROS indigo上安装RGBDSLAM v2 indigo

RGBDSLAM v2是用于RGB-D相机的最先进的SLAM系统，例如Microsoft Kinect或Asus Xtion Pro Live。 您可以使用它来创建3D点云或OctoMaps。

https://github.com/felixendres/rgbdslam_v2

安装libfreenect2和iai_kinect2

https://github.com/OpenKinect/libfree
https://github.com/code-iai/iai_kinect2

创建一个名 rgbdslam_kinect2.launch 的文件，其内容如下

rgbdslam_kinect2.launch:  <launch> <node pkg="rgbdslam" type="rgbdslam" name="rgbdslam" cwd="node" required="true" output="screen"> 

<param name="config/topic_image_depth"             value="/kinect2/qhd/image_depth_rect"/>

<param name="config/topic_points"                  value=""/> <!--if empty, poincloud will be reconstructed from image and depth -->

<!-- These are the default values of some important parameters -->
<param name="config/feature_extractor_type"        value="SIFTGPU"/><!-- also available: SIFT, SIFTGPU, SURF, SURF128 (extended SURF), ORB. -->
<param name="config/feature_detector_type"         value="SIFTGPU"/><!-- 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/optimizer_skip_step"           value="15"/><!-- optimize only every n-th frame -->
<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/backend_solver"                value="csparse"/><!-- pcg is faster and good for continuous online optimization, cholmod and csparse are better for offline optimization (without good initial guess)-->

<param name="config/pose_relative_to"              value="first"/><!-- 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/maximum_depth"           value="2"/>
<param name="config/subscriber_queue_size"         value="20"/>

<param name="config/min_sampled_candidates"        value="30"/><!-- Frame-to-frame comparisons to random frames (big loop closures) -->
<param name="config/predecessor_candidates"        value="20"/><!-- Frame-to-frame comparisons to sequential frames-->
<param name="config/neighbor_candidates"           value="20"/><!-- Frame-to-frame comparisons to graph neighbor frames-->
<param name="config/ransac_iterations"             value="140"/>

<param name="config/g2o_transformation_refinement"           value="1"/>
<param name="config/icp_method"           value="gicp"/>  <!-- icp, gicp ... -->

<!--
<param name="config/max_rotation_degree"           value="20"/>
<param name="config/max_translation_meter"           value="0.5"/>

<param name="config/min_matches"           value="30"/>   

<param name="config/min_translation_meter"           value="0.05"/>
<param name="config/min_rotation_degree"           value="3"/>
<param name="config/g2o_transformation_refinement"           value="2"/>
<param name="config/min_rotation_degree"           value="10"/>

<param name="config/matcher_type"         value="SIFTGPU"/>
 -->
</node>
</launch>

从不同的终端窗口运行roslaunch rgbdslam rgbdslam_kinect2.launch和rosrun kinect2_bridge kinect2_bridge.launch

现在应该出现RGBDSLAM GUI并正常工作。