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Before troubleshooting, confirm that the camera data stream, host software, and algorithm firmware use compatible versions. Record the current configuration before changing parameters so you can restore it if needed.

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Pallet recognition and obstacle avoidance

Possible causeThe point cloud for the black pallet is incomplete.Resolution
  1. In 3D Settings in the host software, set High Exposure to 1400.
    2. In Filter, set Low Signal Threshold to 20.
    3. Set Small Signal Detection to 1.
Possible causeThe host software and embedded algorithm firmware versions do not match.ResolutionUpdate the embedded algorithm firmware.
Possible causeThe ground point cloud was not captured.ResolutionOpen the camera. Set High Exposure to 1400 in 3D Settings, set Low Signal Threshold to 10 in Filter, and run external-parameter calibration. Restore the original values after calibration.
Resolution
  1. Check that the pallet point cloud is complete.
    2. Check that the pallet is approximately 1300 mm from the camera.
Possible causeNo data or insufficient data was received.ResolutionUse the host software to confirm that the camera produces images and that the filter settings are not removing too much point-cloud data.
Possible causeThere is not enough point-cloud data to detect the pallet legs.ResolutionCheck for the following conditions:
1. The camera or fork-arm lift height changed.
2. The pallet legs are blocked.
3. The camera or fork arms have excessive pitch.
4. The pallet legs are not imaged clearly.
5. A reflective post is too close to a pallet leg and affects imaging.
Use PalletPro to confirm the condition, then adjust the configuration, reflective post, or forklift pose as needed.
Possible causeThe pallet-leg dimensions do not meet the configured limits, or no pallet leg was detected.ResolutionThe pallet-leg features are outside the recognition range. Adjust the leg-width or pallet-width range if appropriate.
Possible causeThe camera installation height is not configured.ResolutionSet the installation-height parameter or run external-parameter calibration.
Possible causePallet verification failed because the crossbar was not detected or the pallet pitch angle is too large.ResolutionUse the host software to disable flying-pixel removal, move the camera closer by changing the docking distance, or adjust the crossbar detection ratio.
Possible causeThe pallet-leg widths differ too much within the field of view.ResolutionCheck whether a reflective post is near the pallet or whether the pallet is close to a wall and its edge legs are not imaged correctly.
Possible causeThe pallet heading angle in the field of view is too large (> 30°).ResolutionStraighten the pallet before detection.
Resolution
  1. Confirm that the target obstacle-avoidance profile has been configured in advance.
    2. Stop and restart the data stream, then check whether the profile updates.
Possible causeThe algorithm version does not match the product.ResolutionUpgrade the algorithm firmware.
Possible causesFor S2/S2 Max, the pull-up wiring may be missing. For S10/S10 Pro, the algorithm firmware may be too old.Resolution
  1. Add a pull-up resistor for S2/S2 Max as required by the vehicle system.
    2. Upgrade S10/S10 Pro algorithm firmware to V1.1.050E06_250527 or later.
Resolution
  1. Check the host software version.
    2. Check the camera firmware version.
    3. Check that the obstacle-avoidance configuration was applied to the camera.
ResolutionRestart the camera, then enable real-time refresh in Global Settings in the application algorithm software.