Please send the values that you are using with these bash variables.
On that page under v1.3.0 you see:
- Add support for up to 4 ZED X cameras per MAX96712 (require SDK 5.0)
- Add support for up to 2 ZED X cameras per MAX9296 (require SDK 5.0)
Do you have the MAX96712? Mine are in /lib/modules/5.15.148-tegra/updates/drivers/stereolabs
Your driver version specifically mentions MAX96712 but might be worth confirming given exactly 2 work.
Let’s clear things up a bit.
Maxim MAX96712 is the model of the GMSL2 deserializer chip installed on the ZED Link Duo and ZED Link Quad (2x chips) capture cards, not a library.
The ZED Link Mono and the Mini Carrier Board instead use the Maxim MAX9296A.
Regarding the multi-camera issue, I recommend that you all upgrade the ZED X Driver to v1.3.1 and the ZED SDK to v5.0.3.
They both introduce fixes to connectivity problems in multi-camera setups.
I have upgraded my ZED SDK to v5.0.3 and my ZED X Driver to v1.3.1 on my Jetson AGX Orin Dev Kit (L4T version 36.4.3). This time all the topics from my 4 cameras are published but there are warnings in the logs:
[component_container_isolated-2] e[33m[WARN] [1753441403.536702976] [wall.zed_x_0]: Corrupted frame detected: CORRUPTED FRAMEe[0m
[component_container_isolated-2] [2025-07-25 11:03:23 UTC][ZED][WARNING] Frames may be corrupted or degraded
[component_container_isolated-2] e[33m[WARN] [1753441403.677850784] [wall.zed_x_0]: Corrupted frame detected: CORRUPTED FRAMEe[0m
[component_container_isolated-2] [2025-07-25 11:03:23 UTC][ZED][WARNING] Frames may be corrupted or degraded
[component_container_isolated-2] e[33m[WARN] [1753441403.716070016] [wall.zed_x_mini_2]: Corrupted frame detected: CORRUPTED FRAMEe[0m
[component_container_isolated-2] [2025-07-25 11:03:23 UTC][ZED][WARNING] Frames may be corrupted or degraded
[component_container_isolated-2] e[33m[WARN] [1753441403.819320000] [wall.zed_x_mini_2]: Corrupted frame detected: CORRUPTED FRAMEe[0m
[component_container_isolated-2] [2025-07-25 11:03:23 UTC][ZED][WARNING] Frames may be corrupted or degraded
[component_container_isolated-2] e[33m[WARN] [1753441403.885193920] [wall.zed_x_0]: Corrupted frame detected: CORRUPTED FRAMEe[0m
[component_container_isolated-2] [2025-07-25 11:03:23 UTC][ZED][WARNING] Frames may be corrupted or degraded
[component_container_isolated-2] e[33m[WARN] [1753441403.907144832] [wall.zed_x_mini_2]: Corrupted frame detected: CORRUPTED FRAMEe[0m
[component_container_isolated-2] [2025-07-25 11:03:23 UTC][ZED][WARNING] Frames may be corrupted or degraded
[component_container_isolated-2] e[33m[WARN] [1753441403.993550400] [wall.zed_x_mini_2]: Corrupted frame detected: CORRUPTED FRAMEe[0m
[component_container_isolated-2] [2025-07-25 11:03:24 UTC][ZED][WARNING] Frames may be corrupted or degraded
[component_container_isolated-2] [2025-07-25 11:03:24 UTC][ZED][WARNING] Frames may be corrupted or degraded
[component_container_isolated-2] [2025-07-25 11:03:24 UTC][ZED][WARNING] Frames may be corrupted or degraded
[component_container_isolated-2] e[33m[WARN] [1753441404.516945856] [wall.zed_x_mini_2]: Corrupted frame detected: CORRUPTED FRAMEe[0m
[component_container_isolated-2] e[33m[WARN] [1753441404.579967872] [wall.zed_x_0]: Corrupted frame detected: CORRUPTED FRAMEe[0m
[component_container_isolated-2] [2025-07-25 11:03:24 UTC][ZED][WARNING] Frames may be corrupted or degraded
[component_container_isolated-2] [2025-07-25 11:03:24 UTC][ZED][WARNING] Frames may be corrupted or degraded
[component_container_isolated-2] e[33m[WARN] [1753441404.604031872] [wall.zed_x_mini_2]: Corrupted frame detected: CORRUPTED FRAMEe[0m
The launch command that I mentioned earlier is called 4 times in a loop for all the four cameras that I have.
The zedx.yaml file that I use contains:
# config/zedx.yaml
# Parameters for Stereolabs ZED X camera
---
/**:
ros__parameters:
general:
camera_model: 'zedx'
camera_name: 'zedx' # overwritten by launch file
grab_resolution: 'HD1200' # The native camera grab resolution. 'HD1200', 'HD1080', 'SVGA', 'AUTO'
grab_frame_rate: 15 # ZED SDK internal grabbing rate (HD1200/HD1080: 60, 30, 15 - SVGA: 120, 60,>
video:
exposure_time: 16000 # Defines the real exposure time in microseconds. Recommended to control ma>
auto_exposure_time_range_min: 28 # Defines the minimum range of exposure auto control in micro s>
auto_exposure_time_range_max: 30000 # Defines the maximum range of exposure auto control in micr>
exposure_compensation: 50 # Defines the Exposure-target compensation made after auto exposure. R>
analog_gain: 1255 # Defines the real analog gain (sensor) in mDB. Range [1000-16000]. Recommende>
auto_analog_gain_range_min: 1000 # Defines the minimum range of sensor gain in automatic control
auto_analog_gain_range_max: 16000 # Defines the maximum range of sensor gain in automatic control
digital_gain: 1 # Defines the real digital gain (ISP) as a factor. Range [1-256]. Recommended to>
auto_digital_gain_range_min: 1 # Defines the minimum range of digital ISP gain in automatic cont>
auto_digital_gain_range_max: 256 # Defines the maximum range of digital ISP gain in automatic co>
denoising: 50 # Defines the level of denoising applied on both left and right images. Range [0-1>
depth:
min_depth: 0.3 # Min: 0.3, Max: 3.0
max_depth: 10.0 # Max: 20.0
The zedxm.yaml contains:
# config/zedxm_yaml
# Parameters for Stereolabs ZED X Mini camera
---
/**:
ros__parameters:
general:
camera_model: 'zedxm'
camera_name: 'zedxm' # overwritten by launch file
grab_resolution: 'HD1200' # The native camera grab resolution. 'HD1200', 'HD1080', 'SVGA', 'AUTO'
grab_frame_rate: 15 # ZED SDK internal grabbing rate (HD1200/HD1080: 60, 30, 15 - SVGA: 120, 60,>
video:
exposure_time: 16666 # Defines the real exposure time in microseconds. Recommended to control ma>
auto_exposure_time_range_min: 28 # Defines the minimum range of exposure auto control in micro s>
auto_exposure_time_range_max: 16666 # Defines the maximum range of exposure auto control in micr>
exposure_compensation: 50 # Defines the Exposure-target compensation made after auto exposure. R>
analog_gain: 8000 # Defines the real analog gain (sensor) in mDB. Range [1000-16000]. Recommende>
auto_analog_gain_range_min: 1000 # Defines the minimum range of sensor gain in automatic control
auto_analog_gain_range_max: 16000 # Defines the maximum range of sensor gain in automatic control
digital_gain: 128 # Defines the real digital gain (ISP) as a factor. Range [1-256]. Recommended >
auto_digital_gain_range_min: 1 # Defines the minimum range of digital ISP gain in automatic cont>
auto_digital_gain_range_max: 256 # Defines the maximum range of digital ISP gain in automatic co>
denoising: 50 # Defines the level of denoising applied on both left and right images. Range [0-1>
depth:
min_depth: 0.3 # Min: 0.3, Max: 3.0
max_depth: 10.0 # Max: 20.0
The common_stereo.yaml file contains:
# config/common_stereo.yaml
# Common parameters to Stereolabs ZED Stereo cameras
---
/**:
ros__parameters:
use_sim_time: false # Set to `true` only if there is a publisher for the simulated clock to the `/clock` topic. Normally used in simulation mode.
simulation:
sim_enabled: false # Set to `true` to enable the simulation mode and connect to a simulation server
sim_address: '127.0.0.1' # The connection address of the simulation server. See the documentation of the supported simulation plugins for more information.
sim_port: 30000 # The connection port of the simulation server. See the documentation of the supported simulation plugins for more information.
svo:
use_svo_timestamps: true # Use the SVO timestamps to publish data. If false, data will be published at the system time.
publish_svo_clock: false # [overwritten by launch file options] When use_svo_timestamps is true allows to publish the SVO clock to the `/clock` topic. This is useful for synchronous rosbag playback.
svo_loop: false # Enable loop mode when using an SVO as input source. NOTE: ignored if SVO timestamping is used
svo_realtime: false # if true the SVO will be played trying to respect the original framerate eventually skipping frames, otherwise every frame will be processed respecting the `pub_frame_rate` setting
play_from_frame: 0 # Start playing the SVO from a specific frame
replay_rate: 1.0 # Replay rate for the SVO when not used in realtime mode (between [0.10-5.0])
general:
camera_timeout_sec: 5
camera_max_reconnect: 5
camera_flip: false
self_calib: true # Enable the self-calibration process at camera opening. See https://www.stereolabs.com/docs/api/structsl_1_1InitParameters.html#affeaa06cfc1d849e311e484ceb8edcc5
serial_number: 0 # overwritten by launch file
pub_resolution: 'CUSTOM' # The resolution used for image and depth map publishing. 'NATIVE' to use the same `general.grab_resolution` - `CUSTOM` to apply the `general.pub_downscale_factor` downscale factory to reduce bandwidth in transmission
pub_downscale_factor: 2.0 # rescale factor used to rescale image before publishing when 'pub_resolution' is 'CUSTOM'
pub_frame_rate: 15.0 # frequency of publishing of visual images and depth images
enable_image_validity_check: 1 # [SDK5 required] Sets the image validity check. If set to 1, the SDK will check if the frames are valid before processing.
gpu_id: -1
optional_opencv_calibration_file: '' # Optional path where the ZED SDK can find a file containing the calibration information of the camera computed by OpenCV. Read the ZED SDK documentation for more information: https://www.stereolabs.com/docs/api/structsl_1_1InitParameters.html#a9eab2753374ef3baec1d31960859ba19
async_image_retrieval: false # Enable/disable the asynchronous image retrieval - Note: enable only to improve SVO recording performance
video:
brightness: 4 # [DYNAMIC] Not available for ZED X/ZED X Mini
contrast: 4 # [DYNAMIC] Not available for ZED X/ZED X Mini
hue: 0 # [DYNAMIC] Not available for ZED X/ZED X Mini
saturation: 4 # [DYNAMIC]
sharpness: 4 # [DYNAMIC]
gamma: 8 # [DYNAMIC]
auto_exposure_gain: true # [DYNAMIC]
exposure: 80 # [DYNAMIC]
gain: 80 # [DYNAMIC]
auto_whitebalance: true # [DYNAMIC]
whitebalance_temperature: 42 # [DYNAMIC] - [28,65] x100 - works only if `auto_whitebalance` is false
sensors:
publish_imu_tf: false # [overwritten by launch file options] enable/disable the IMU TF broadcasting
sensors_image_sync: false # Synchronize Sensors messages with latest published video/depth message
sensors_pub_rate: 100. # frequency of publishing of sensors data. MAX: 400. - MIN: grab rate
region_of_interest:
automatic_roi: false # Enable the automatic ROI generation to automatically detect part of the robot in the FoV and remove them from the processing. Note: if enabled the value of `manual_polygon` is ignored
depth_far_threshold_meters: 2.5 # Filtering how far object in the ROI should be considered, this is useful for a vehicle for instance
image_height_ratio_cutoff: 0.5 # By default consider only the lower half of the image, can be useful to filter out the sky
#manual_polygon: '[]' # A polygon defining the ROI where the ZED SDK perform the processing ignoring the rest. Coordinates must be normalized to '1.0' to be resolution independent.
#manual_polygon: '[[0.25,0.33],[0.75,0.33],[0.75,0.5],[0.5,0.75],[0.25,0.5]]' # A polygon defining the ROI where the ZED SDK perform the processing ignoring the rest. Coordinates must be normalized to '1.0' to be resolution independent.
#manual_polygon: '[[0.25,0.25],[0.75,0.25],[0.75,0.75],[0.25,0.75]]' # A polygon defining the ROI where the ZED SDK perform the processing ignoring the rest. Coordinates must be normalized to '1.0' to be resolution independent.
#manual_polygon: '[[0.5,0.25],[0.75,0.5],[0.5,0.75],[0.25,0.5]]' # A polygon defining the ROI where the ZED SDK perform the processing ignoring the rest. Coordinates must be normalized to '1.0' to be resolution independent.
apply_to_depth: true # Apply ROI to depth processing
apply_to_positional_tracking: true # Apply ROI to positional tracking processing
apply_to_object_detection: true # Apply ROI to object detection processing
apply_to_body_tracking: true # Apply ROI to body tracking processing
apply_to_spatial_mapping: true # Apply ROI to spatial mapping processing
depth:
depth_mode: 'NEURAL_PLUS' # Matches the ZED SDK setting: 'NONE', 'PERFORMANCE', 'QUALITY', 'ULTRA', 'NEURAL', 'NEURAL_PLUS' - Note: if 'NONE' all the modules that requires depth extraction are disabled by default (Pos. Tracking, Obj. Detection, Mapping, ...)
depth_stabilization: 30 # Forces positional tracking to start if major than 0 - Range: [0,100]
openni_depth_mode: false # 'false': 32bit float [meters], 'true': 16bit unsigned int [millimeters]
point_cloud_freq: 15.0 # [DYNAMIC] - frequency of the pointcloud publishing (equal or less to `pub_frame_rate` value)
point_cloud_res: 'COMPACT' # The resolution used for point cloud publishing - 'COMPACT'-Standard resolution. Optimizes processing and bandwidth, 'REDUCED'-Half resolution. Low processing and bandwidth requirements
depth_confidence: 95 # [DYNAMIC]
depth_texture_conf: 100 # [DYNAMIC]
remove_saturated_areas: true # [DYNAMIC]
pos_tracking:
pos_tracking_enabled: true # True to enable positional tracking from start
pos_tracking_mode: 'GEN_1' # Matches the ZED SDK setting: 'GEN_1', 'GEN_2'
imu_fusion: true # enable/disable IMU fusion. When set to false, only the optical odometry will be used.
publish_tf: true # [overwritten by launch file options] publish `odom -> camera_link` TF
publish_map_tf: true # [overwritten by launch file options] publish `map -> odom` TF
map_frame: 'map'
odometry_frame: 'odom'
area_memory_db_path: ''
area_memory: true # Enable to detect loop closure
reset_odom_with_loop_closure: true # Re-initialize odometry to the last valid pose when loop closure happens (reset camera odometry drift)
depth_min_range: 0.0 # Set this value for removing fixed zones of the robot in the FoV of the camerafrom the visual odometry evaluation
set_as_static: false # If 'true' the camera will be static and not move in the environment
set_gravity_as_origin: true # If 'true' align the positional tracking world to imu gravity measurement. Keep the yaw from the user initial pose.
floor_alignment: false # Enable to automatically calculate camera/floor offset
initial_base_pose: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # Initial position of the `camera_link` frame in the map -> [X, Y, Z, R, P, Y]
path_pub_rate: 2.0 # [DYNAMIC] - Camera trajectory publishing frequency
path_max_count: -1 # use '-1' for unlimited path size
two_d_mode: false # Force navigation on a plane. If true the Z value will be fixed to 'fixed_z_value', roll and pitch to zero
fixed_z_value: 0.00 # Value to be used for Z coordinate if `two_d_mode` is true
transform_time_offset: 0.0 # The value added to the timestamp of `map->odom` and `odom->camera_link` transform being generated
reset_pose_with_svo_loop: true # Reset the camera pose the `initial_base_pose` when the SVO loop is enabled and the SVO playback reaches the end of the file.
gnss_fusion:
gnss_fusion_enabled: false # fuse 'sensor_msg/NavSatFix' message information into pose data
gnss_fix_topic: '/fix' # Name of the GNSS topic of type NavSatFix to subscribe [Default: '/gps/fix']
gnss_zero_altitude: false # Set to `true` to ignore GNSS altitude information
h_covariance_mul: 1.0 # Multiplier factor to be applied to horizontal covariance of the received fix (plane X/Y)
v_covariance_mul: 1.0 # Multiplier factor to be applied to vertical covariance of the received fix (Z axis)
publish_utm_tf: true # Publish `utm` -> `map` TF
broadcast_utm_transform_as_parent_frame: false # if 'true' publish `utm` -> `map` TF, otherwise `map` -> `utm`
enable_reinitialization: false # determines whether reinitialization should be performed between GNSS and VIO fusion when a significant disparity is detected between GNSS data and the current fusion data. It becomes particularly crucial during prolonged GNSS signal loss scenarios.
enable_rolling_calibration: true # If this parameter is set to true, the fusion algorithm will used a rough VIO / GNSS calibration at first and then refine it. This allow you to quickly get a fused position.
enable_translation_uncertainty_target: false # When this parameter is enabled (set to true), the calibration process between GNSS and VIO accounts for the uncertainty in the determined translation, thereby facilitating the calibration termination. The maximum allowable uncertainty is controlled by the 'target_translation_uncertainty' parameter.
gnss_vio_reinit_threshold: 5.0 # determines the threshold for GNSS/VIO reinitialization. If the fused position deviates beyond out of the region defined by the product of the GNSS covariance and the gnss_vio_reinit_threshold, a reinitialization will be triggered.
target_translation_uncertainty: 10e-2 # defines the target translation uncertainty at which the calibration process between GNSS and VIO concludes. By default, the threshold is set at 10 centimeters.
target_yaw_uncertainty: 1e-2 # defines the target yaw uncertainty at which the calibration process between GNSS and VIO concludes. The unit of this parameter is in radian. By default, the threshold is set at 0.1 radians.
mapping:
mapping_enabled: false # True to enable mapping and fused point cloud pubblication
resolution: 0.05 # maps resolution in meters [min: 0.01f - max: 0.2f]
max_mapping_range: 5.0 # maximum depth range while mapping in meters (-1 for automatic calculation) [2.0, 20.0]
fused_pointcloud_freq: 1.0 # frequency of the publishing of the fused colored point cloud
clicked_point_topic: '/clicked_point' # Topic published by Rviz when a point of the cloud is clicked. Used for plane detection
pd_max_distance_threshold: 0.15 # Plane detection: controls the spread of plane by checking the position difference.
pd_normal_similarity_threshold: 15.0 # Plane detection: controls the spread of plane by checking the angle difference.
object_detection:
od_enabled: false # True to enable Object Detection
model: 'MULTI_CLASS_BOX_FAST' # 'MULTI_CLASS_BOX_FAST', 'MULTI_CLASS_BOX_MEDIUM', 'MULTI_CLASS_BOX_ACCURATE', 'PERSON_HEAD_BOX_FAST', 'PERSON_HEAD_BOX_ACCURATE', 'CUSTOM_YOLOLIKE_BOX_OBJECTS'
custom_onnx_file: '' # Only used if 'model' is 'CUSTOM_YOLOLIKE_BOX_OBJECTS'. Path to the YOLO-like ONNX file for custom object detection directly performed by the ZED SDK.
custom_onnx_input_size: 512 # Resolution used with the YOLO-like ONNX file. For example, 512 means a input tensor '1x3x512x512'
custom_label_yaml: '' # Only used if 'model' is 'CUSTOM_YOLOLIKE_BOX_OBJECTS'. Path to the COCO-like YAML file storing the custom class labels.
allow_reduced_precision_inference: true # Allow inference to run at a lower precision to improve runtime and memory usage
max_range: 20.0 # [m] Defines a upper depth range for detections
confidence_threshold: 75.0 # [DYNAMIC] - Minimum value of the detection confidence of an object [0,99]
prediction_timeout: 0.5 # During this time [sec], the object will have OK state even if it is not detected. Set this parameter to 0 to disable SDK predictions
enable_tracking: true # Defines if the object detection will track objects across images flow
filtering_mode: 1 # '0': NONE - '1': NMS3D - '2': NMS3D_PER_CLASS
mc_people: true # [DYNAMIC] - Enable/disable the detection of persons for 'MULTI_CLASS_X' models
mc_vehicle: true # [DYNAMIC] - Enable/disable the detection of vehicles for 'MULTI_CLASS_X' models
mc_bag: true # [DYNAMIC] - Enable/disable the detection of bags for 'MULTI_CLASS_X' models
mc_animal: true # [DYNAMIC] - Enable/disable the detection of animals for 'MULTI_CLASS_X' models
mc_electronics: true # [DYNAMIC] - Enable/disable the detection of electronic devices for 'MULTI_CLASS_X' models
mc_fruit_vegetable: true # [DYNAMIC] - Enable/disable the detection of fruits and vegetables for 'MULTI_CLASS_X' models
mc_sport: true # [DYNAMIC] - Enable/disable the detection of sport-related objects for 'MULTI_CLASS_X' models
body_tracking:
bt_enabled: false # True to enable Body Tracking
model: 'HUMAN_BODY_MEDIUM' # 'HUMAN_BODY_FAST', 'HUMAN_BODY_MEDIUM', 'HUMAN_BODY_ACCURATE'
body_format: 'BODY_38' # 'BODY_18','BODY_34','BODY_38','BODY_70'
allow_reduced_precision_inference: false # Allow inference to run at a lower precision to improve runtime and memory usage
max_range: 20.0 # [m] Defines a upper depth range for detections
body_kp_selection: 'FULL' # 'FULL', 'UPPER_BODY'
enable_body_fitting: false # Defines if the body fitting will be applied
enable_tracking: true # Defines if the object detection will track objects across images flow
prediction_timeout_s: 0.5 # During this time [sec], the skeleton will have OK state even if it is not detected. Set this parameter to 0 to disable SDK predictions
confidence_threshold: 50.0 # [DYNAMIC] - Minimum value of the detection confidence of skeleton key points [0,99]
minimum_keypoints_threshold: 5 # [DYNAMIC] - Minimum number of skeleton key points to be detected for a valid skeleton
stream_server:
stream_enabled: false # enable the streaming server when the camera is open
codec: 'H264' # different encoding types for image streaming: 'H264', 'H265'
port: 30000 # Port used for streaming. Port must be an even number. Any odd number will be rejected.
bitrate: 12500 # [1000 - 60000] Streaming bitrate (in Kbits/s) used for streaming. See https://www.stereolabs.com/docs/api/structsl_1_1StreamingParameters.html#a873ba9440e3e9786eb1476a3bfa536d0
gop_size: -1 # [max 256] The GOP size determines the maximum distance between IDR/I-frames. Very high GOP size will result in slightly more efficient compression, especially on static scenes. But latency will increase.
adaptative_bitrate: false # Bitrate will be adjusted depending the number of packet dropped during streaming. If activated, the bitrate can vary between [bitrate/4, bitrate].
chunk_size: 16084 # [1024 - 65000] Stream buffers are divided into X number of chunks where each chunk is chunk_size bytes long. You can lower chunk_size value if network generates a lot of packet lost: this will generates more chunk for a single image, but each chunk sent will be lighter to avoid inside-chunk corruption. Increasing this value can decrease latency.
target_framerate: 0 # Framerate for the streaming output. This framerate must be below or equal to the camera framerate. Allowed framerates are 15, 30, 60 or 100 if possible. Any other values will be discarded and camera FPS will be taken.
advanced: # WARNING: do not modify unless you are confident of what you are doing
# Reference documentation: https://man7.org/linux/man-pages/man7/sched.7.html
thread_sched_policy: 'SCHED_BATCH' # 'SCHED_OTHER', 'SCHED_BATCH', 'SCHED_FIFO', 'SCHED_RR' - NOTE: 'SCHED_FIFO' and 'SCHED_RR' require 'sudo'
thread_grab_priority: 50 # ONLY with 'SCHED_FIFO' and 'SCHED_RR' - [1 (LOW) z-> 99 (HIGH)] - NOTE: 'sudo' required
thread_sensor_priority: 70 # ONLY with 'SCHED_FIFO' and 'SCHED_RR' - [1 (LOW) z-> 99 (HIGH)] - NOTE: 'sudo' required
thread_pointcloud_priority: 60 # ONLY with 'SCHED_FIFO' and 'SCHED_RR' - [1 (LOW) z-> 99 (HIGH)] - NOTE: 'sudo' required
debug:
sdk_verbose: 1 # Set the verbose level of the ZED SDK
sdk_verbose_log_file: '' # Path to the file where the ZED SDK will log its messages. If empty, no file will be created. The log level can be set using the `sdk_verbose` parameter.
debug_common: false
debug_sim: false
debug_video_depth: false
debug_camera_controls: false
debug_point_cloud: false
debug_positional_tracking: false
debug_gnss: false
debug_sensors: false
debug_mapping: false
debug_terrain_mapping: false
debug_object_detection: false
debug_body_tracking: false
debug_roi: false
debug_streaming: false
debug_advanced: false
Now aswering your question about the values used in the bash launch command:
The launch command is called in a loop 4 times where it launches all the 4 cameras one by one.
For the ZEDX camera the camera_model is passed with zedx and the camera_config_path is passed the path to the zedx.yaml file that I shared above, the common_config_path was passed with the path to the common_stero.yaml file, the serial number with the serial number of the camera [40919615] and finally the namespace and camera name with wall and zed_x_0.
The other three zedxm cameras are launched similarly but with the camera_config_path having the path to the zedxm.yaml file and their respective serial numbers, namespace, camera name and camera model (Please see the logs above).
Why do I have this warning of Frames may be corrupted or degraded?
However I can render the rgb data from all the 4 cameras in rviz.
This warning is issued because the image validity check is enabled by default and the camera is probably looking at something that is too close and is covering the most of the field of view.
Please send the picture of what the cameras are seeing. They will be useful to learn more concerning why the warning is issued.
This is a good indicator that the system is working.