I installed rgbdslam and octomap. Have been trying to run rgbdslam with octomap. Eventual goal is to get the MarkerArray /occupied_cells_vis_array as it should. Some things I've done:
METHOD 1
- Tried to run kinect+rgbdslam.launch and octomap_server.launch.
- Open rviz and nothing is received on the
/octomap_point_cloud_array,/occupied_cells_vis_array,/rgbdslam/aggregate_cloudsOR/rgbdslam/batch_clouds. The only PointCloud2 topics that displays an output are/camera/depth_registered/points.
METHOD 2
- Tried to run rgbdslam_octomap.launch. Worked as well, but due to the color_octomap_server_node not found under octomap_server package (I believe there are some posts saying that you need the experimental version of octomap and some posts saying that the octomap_server is by default colored) I edited it so that it reads octomap_server_node.
- Runs as well, also gives the same problem as above.
METHOD 3
While invoking the above scenario, I ran the following commands:
Runningroswtf
gives that node subscription is unconnected:
*/rgbdslam:
*/cloud_in
Running rosrun tf view_frames
gives camera_link > /camera_rgb_frame > /camera_rgb_optical_frame and camera_link > /camera_depth_frame > /camera_depth_optical_frame. Two branches only.
Runningrostopic_list
The expect topics are listed:
/cloud_in
/octomap_point_cloud_array
/occupied_cells_vis_array
/rgbdslam/batch_clouds
/rgbdslam/aggregate_clouds
/tf
Running rosservice call /rgbdslam/ros_ui send_all did not change the above results.
I think it is a mapping issue and that the point clouds are not transformed to the correct topics. I am not sure which point cloud problem it is. Please give some pointers as how I can solve this problem.
EDIT 05/28/14 +1h: The issue lies in the transform. /map is not present in my frames.pdf view. Not sure how to solve this problem either.
EDIT 06/04/14: Solved building octomap using rgbdslam data by recording a .bag file, launching octomap_server, and viewing it in RViz. No fix for continuous rgbdslam mapping and trajectory output found yet.
rgbdslam_octomap.launch
<launch>
<env name="ROSCONSOLE_CONFIG_FILE" value="$(find rgbdslam)/log.conf"/>
<!--might only work with the experimental octomap (as of May 11)-->
<include file="$(find openni_launch)/launch/openni.launch"/>
<node pkg="rgbdslam" type="rgbdslam" name="rgbdslam" cwd="node" required="false" output="log" >
<param name="config/topic_image_mono" value="/camera/rgb/image_color"/>
<param name="config/topic_points" value="/camera/rgb/points"/> <!--if empty, poincloud will be reconstructed from image and depth -->
<param name="config/wide_topic" value=""/>;
<param name="config/wide_cloud_topic" value=""/>;
<param name="config/drop_async_frames" value="true"/> <!-- Check association of depth and visual image, reject if not in sync -->
<param name="config/feature_detector_type" value="SIFTGPU"/><!-- If SIFTGPU is enabled in CMakeLists.txt, use SURF here -->
<param name="config/feature_extractor_type" value="SIFTGPU"/><!-- If SIFTGPU is enabled in CMakeLists.txt, use SURF here -->
<param name="config/matcher_type" value="FLANN"/> <!-- FLANN (not avail for ORB features), SIFTGPU (only for SIFTGPU detector) or BRUTEFORCE-->
<param name="config/max_keypoints" value="700"/><!-- Extract no more than this many keypoints (not honored by SIFTGPU)-->
<param name="config/min_keypoints" value="300"/><!-- Extract no less than this many ... -->
<param name="config/nn_distance_ratio" value="0.6"/> <!-- Feature correspondence is valid if distance to nearest neighbour is smaller than this parameter times the distance to the 2nd neighbour -->
<param name="config/optimizer_skip_step" value="1"/><!-- optimize every n-th frame -->
<param name="config/optimizer_iterations" value="4"/><!-- optimize every n-th frame -->
<param name="config/store_pointclouds" value="true"/> <!-- if, e.g., only trajectory is required, setting this to false saves lots of memory -->
<param name="config/backend_solver" value="pcg"/>
<param name="config/individual_cloud_out_topic" value="/rgbdslam/batch_clouds"/>;
<param name="config/visualization_skip_step" value="1"/> <!-- draw only every nth pointcloud row and line, high values require higher squared_meshing_threshold -->
<param name="config/send_clouds_rate" value="2"/> <!-- When sending the point clouds (e.g. to RVIZ or Octomap Server) limit sending to this many clouds per second -->
<param name="config/min_time_reported" value="0.01"/><!-- for easy runtime analysis -->
<param name="config/min_translation_meter" value="0.05"/><!-- frames with motion less than this, will be omitted -->
<param name="config/min_rotation_degree" value="1"/><!-- frames with motion less than this, will be omitted -->
<param name="config/predecessor_candidates" value="5"/><!-- search through this many immediate predecessor nodes for corrspondences -->
<param name="config/neighbor_candidates" value="5"/><!-- search through this many graph neighbour nodes for corrspondences -->
<param name="config/min_sampled_candidates" value="5"/><!-- search through this many uniformly sampled nodes for corrspondences -->
</node>
<!-- Launch octomap_server for mappingL: Listens to incoming PointCloud2 data
and incrementally build an octomap. The data is sent out in different representations. -->
<node pkg="octomap_server" type="octomap_server_node" name="octomap_server" output="screen">
<param name="resolution" value="0.005" />
<!-- fixed map frame (set to 'map' if SLAM or localization running!) -->
<param name="frame_id" type="string" value="map" />
<!-- maximum range to integrate (speedup, accuracy) -->
<param name="max_sensor_range" value="6.0" />
<!-- Save octomap here on destruction of the server -->
<param name="save_directory" value="$(optenv OCTOMAP_SAVE_DIR ./)" />
<!-- data source to integrate (PointCloud2) -->
<remap from="cloud_in" to="/rgbdslam/batch_clouds" />
</node>
</launch>
Originally posted by xuningy on ROS Answers with karma: 101 on 2014-05-28
Post score: 1