![]() However using rtabmap_viz, the interface should look like the tutorials of the standalone version. With the RVIZ plugin rtabmap/MapCloud, the clouds can be incrementally added to RVIZ. There are two choices for online visualization: rtabmap_viz or rviz. $ roslaunch depthai_examples stereo_inertial_node.launch depth_aligned:=false.Imu/data:=/stereo_inertial_publisher/imu/data \ Imu/data_raw:=/stereo_inertial_publisher/imu \ $ roslaunch depthai_examples stereo_inertial_node.launch.Kinect for Azure: see Mapping mode below. $ roslaunch mynt_eye_ros_wrapper mynteye.launch.$ roslaunch realsense2_camera rs_d400_and_t265.launch.$ rosrun imu_filter_madgwick imu_filter_node \īased on your setup, make sure to edit the static transform between the cameras in that launch file. Unite_imu_method:="linear_interpolation" \ $ roslaunch realsense2_camera rs_camera.launch \ # ISSUE: Use unite_imu_method:="copy" if imu topics keep stopping.$ roslaunch realsense2_camera rs_camera.launch align_depth:=true.Image_raw:=/camera/depth/points/image_raw \ $ rosrun rtabmap_util pointcloud_to_depthimage \ To get registration without empty lines $ roslaunch realsense_camera zr300_nodelet_rgdb.launch $ roslaunch realsense_camera r200_nodelet_rgbd.launch Note: the repeating depth_confidence is not an error, it seems on the first call nothing happens, we need to redo second time with a different value. To avoid map -> odom TF published by zed, set tracking/publish_map_tf to false for zed_wrapper_node Rosrun dynamic_reconfigure dynparam set /zed2/zed_node depth_confidence 100 Rosrun dynamic_reconfigure dynparam set /zed2/zed_node depth_texture_conf 90 Rosrun dynamic_reconfigure dynparam set /zed2/zed_node depth_confidence 99 Rosrun dynamic_reconfigure dynparam set zed_node depth_confidence 100 Rosrun dynamic_reconfigure dynparam set zed_node depth_texture_conf 90 Rosrun dynamic_reconfigure dynparam set zed_node depth_confidence 99 ![]() Stereolabs ZED (make sure you have this pull request to avoid synchronization issues) Updated April 29 2020 $ roslaunch kinect2_bridge kinect2_bridge.launch publish_tf:=true.Make sure it is calibrated: see kinect2_calibration. $ roslaunch openni2_launch openni2.launch depth_registration:=true.$ roslaunch freenect_launch freenect.launch depth_registration:=true.$ roslaunch openni_launch openni.launch depth_registration:=true or.The RGB-D sensors which are OpenNI and OpenNI2 compliant would work out-of-the-box using openni_launch, openni2_launch, freenect_launch, iai_kinect2 or Zed packages.
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