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Thx for the db, there are some observations that we can make (referring to figure below):

• The camera is very close to ground, so that the field of view is filled with more than 50% of repetitive symmetric pattern, very difficult to get good depth estimation as well for visual odometry. It is why the ground is poorly represented in the occupancy grid.

• The resulting depth image from the sensor is quite noisy (see top view of the cloud on right image). I suggest to use Grid/3D=false and Grid/RayTracing=true to get more empty cells (see grid on left image):

  $ roslaunch rtabmap_ros rtabmap.launch rtabmap_args:="--delete_db_on_start --Grid/3D false --Grid/RayTracing true" depth_topic:=/camera/aligned_depth_to_color/image_raw rgb_topic:=/camera/color/image_raw camera_info_topic:=/camera/color/camera_info approx_sync:=false
  

• There is quite motion blur when the robot moves (see top middle image, open image in another tab to zoom in), which would affect visual odometry accuracy.

Solutions:

• Tilt the camera toward the ceiling (and/or increase height) so that there is less ground in the FOV of the camera. Make sure to update TF as well between base_link and camera_link.

• Consider using wheel odometry if possible

Thx for the db, there are some observations that we can make (referring to figure below):

• The camera is very close to ground, so that the field of view is filled with more than 50% of repetitive symmetric pattern, very difficult to get good depth estimation as well for visual odometry. It is why the ground is poorly represented in the occupancy grid.

• The resulting depth image from the sensor is quite noisy (see top view of the cloud on right image). I suggest to use Grid/3D=false and Grid/RayTracing=true to get more empty cells (see grid on left image):

  $ roslaunch rtabmap_ros rtabmap.launch rtabmap_args:="--delete_db_on_start --Grid/3D false --Grid/RayTracing true" depth_topic:=/camera/aligned_depth_to_color/image_raw rgb_topic:=/camera/color/image_raw camera_info_topic:=/camera/color/camera_info approx_sync:=false
  

• There is quite motion blur when the robot moves (see top middle image, open image in another tab to zoom in), which would affect visual odometry accuracy.

Solutions:

• Tilt the camera toward the ceiling (and/or increase height) so that there is less ground in the FOV of the camera. Make sure to update TF as well between base_link and camera_link.

• Move slower to limit motion blur

• Consider using wheel odometry if possible

Thx for the db, there are some observations that we can make (referring to figure below):

• The camera is very close to ground, so that the field of view is filled with more than 50% of repetitive symmetric pattern, very difficult to get good depth estimation as well for visual odometry. It is why the ground is poorly represented in the occupancy grid.

• The resulting depth image from the sensor is quite noisy (see top view of the cloud on right image). I suggest to use Grid/3D=false and Grid/RayTracing=true to get more empty cells (see grid on left image):

  $ roslaunch rtabmap_ros rtabmap.launch rtabmap_args:="--delete_db_on_start --Grid/3D false --Grid/RayTracing true" depth_topic:=/camera/aligned_depth_to_color/image_raw rgb_topic:=/camera/color/image_raw camera_info_topic:=/camera/color/camera_info approx_sync:=false
  

• There is quite motion blur when the robot moves (see top middle image, open image in another tab to zoom in), which would affect visual odometry accuracy.

Solutions:Possible solutions:

• Tilt the camera toward the ceiling (and/or increase height) so that there is less ground in the FOV of the camera. Make sure to update TF as well between base_link and camera_link.

• Move slower to limit motion blur

• Consider using wheel odometry if possible