Improve the Aruco detection performance and integrate it into the sima localization pipeline.
There are a few tasks to do:
-
Investigate the cause of unstable/oscillating Aruco detection
- Analyze frame-to-frame fluctuation issues.
- Check camera calibration accuracy, lighting condition, frame rate, and detection logic.
-
Optimize parameters or algorithm to reduce detection error (< 1 cm target)
- Tune detector configuration (corner refinement, dictionary type, thresholding, etc.).
- Explore filtering/smoothing methods (Kalman filter, averaging, pose estimation enhancements).
- Evaluate result accuracy under different environments.
-
Integrate the improved Aruco detection into the sima localization system
- Define interface and coordinate transformation.
- Ensure real-time performance and compatibility with the localization module.
- Perform integration testing and validation.
Please work this task on feat/sima_localization
If you have any questions or ideas, please feel free to bring them up as soon as possible.
Improve the Aruco detection performance and integrate it into the sima localization pipeline.
There are a few tasks to do:
Investigate the cause of unstable/oscillating Aruco detection
Optimize parameters or algorithm to reduce detection error (< 1 cm target)
Integrate the improved Aruco detection into the sima localization system
Please work this task on
feat/sima_localizationIf you have any questions or ideas, please feel free to bring them up as soon as possible.