Using the Orbbec ROS package to get lower CPU usage
This section shows you how to reduce CPU usage for one or more cameras in a ROS 2 environment. This method only works with Gemini 330 series cameras, and the firmware version needs to be above 1.4.10(device_preset is set to Default).
The example launch files used in this section are gemini_330_series_lower_cpu_usage.launch.py and multi_camera_lower_cpu_usage.launch.py.
Parameters that affect CPU usage
-
uvc_backend:Global UVC Backend select on Linux,optional values: libuvc, v4l2.(v4l2 is lower) -
color_format:Color stream coding format.(RGB is lower) -
depth_registration: Enables alignment of the depth frame to the color frame.(align_mode is set to HW lower) -
enable_point_cloud:Enables the point cloud -
enable_colored_point_cloud:Enables the RGB point cloud -
filter:decimation_filter,hdr_merge,sequenced_filter,threshold_filter,hardware_noise_removal_filter,noise_removal_filter,spatial_filter,temporal_filter,hole_filling_filter.(hardware_noise_removal_filter is lower)
Data comparison
Since different machines and different software environments will result in different CPU usage, the CPU improvement rate is calculated based on the device's CPU benchmark. A comparing B:
CPU improvement rate=（CPUA-CPUB）/CPUB*100
In this example, we used two different video stream resolutions as test benchmarks to provide a performance comparison between lower and higher resolutions.(Currently, data is only provided for uvc_backend, color_format, and some filter)
Depth&Left_ir&Right_ir 424 * 266 15fps,Color 848 * 480 15fps
uvc_backend
libuvc comparing v4l2 In the same environment, CPU improvement rate is 13.1%
- libuvc is 72.3%
- v4l2 is 62.8%
color_format
ROS2 color stream sets MJPG encoding format and decodes it to RGB comparing RGB encoding format (including YUYV format to RGB conversion operation cost).The CPU improvement rate under the libuvc protocol is 14.2% the CPU improvement rate under the v4l2 protocol is 30.8%
- libuvc:RGB encoding format is 63.3%，MJPG encoding format and decoded into RGB is 72.3%
- v4l2:RGB encoding format is 48%，MJPG encoding format and decoded into RGB is 62.8%
filter
The color stream setting RGB encoding and MJPG have no effect on filtering and are basically the same. The CPU usage of the depth stream is basically the same under the configuration of 424*266 15fps.
| Filter Configuration | libuvc(CPU improvement rate) | v4l2(CPU improvement rate) |
|---|---|---|
| No filter | 63.3%(0%) | 48.0%(0%) |
| hardware_noise_removal_filter | 61.2%(-3.3%) | 47.9%(-0.2%) |
| hardware_noise_removal_filter+spatial_filter | 65.3%(3.2%) | 51.2%(6.7%) |
| noise_removal_filter | 77.0%(21.6%) | 53.3%(11.0%) |
| noise_removal_filter+spatial_filter | 78.4%(23.9%) | 54.8%(14.2%) |
Depth&Left_ir&Right_ir 848 * 480 30fps,Color 848 * 480 30fps
uvc_backend
libuvc comparing v4l2 In the same environment, CPU improvement rate is 53.9%
- libuvc is 182.8%
- v4l2 is 118.8%
color_format
ROS2 color stream sets MJPG encoding format and decodes it to RGB comparing RGB encoding format (including YUYV format to RGB conversion operation cost).The CPU improvement rate under the libuvc protocol is 90.2% the CPU improvement rate under the v4l2 protocol is 43.1%
- libuvc:RGB encoding format is 182.8%，MJPG encoding format and decoded into RGB is 347.7%
- v4l2:RGB encoding format is 118.8%，MJPG encoding format and decoded into RGB is 170.0%
filter
When the depth stream is configured at 848*480 30fps, the CPU usage is significantly different.
| Filter Configuration | libuvc(CPU improvement rate) | v4l2(CPU improvement rate) |
|---|---|---|
| No filter | 182.8%(0%) | 118.8%(0%) |
| hardware_noise_removal_filter | 186.3%(1.9%) | 115.4%(-2.9%) |
| hardware_noise_removal_filter+spatial_filter | 251.3%(37.5%) | 152.5%(28.4%) |
| noise_removal_filter | 218.0%(16.1%) | 128.5%(8.2%) |
| noise_removal_filter+spatial_filter | 469.6%(156.9%) | 336.7%(183.4%) |
Example launch
This is the current example file for running the camera to achieve the lowest CPU usage, excluding the impact of filters.
Use the following command to start the single-camera configuration:
ros2 launch orbbec_camera gemini_330_series_lower_cpu_usage.launch.py
Use the following command to start the multi-camera configuration:
roslaunch orbbec_camera multi_camera_lower_cpu_usage.launch.py