SLAMFuse feature Timeline ❗
nikolaradulov opened this issue · 0 comments
Issue Description
Title: Merge New Features into Main SLAMFuse Branch
Description:
The objective of this issue is to integrate new features into the main SLAMFuse branch. This integration involves merging the fuzzing mechanism for the camera from the image_filter
branch into the SLAMFuse
branch. Additionally, updates need to be made to the docker files for algorithms, documentation for the fuzzing mechanism, and the dependency list.
Tasks:
-
Merge Fuzzing Mechanism for Camera: Integrate the fuzzing mechanism implemented in the
image_filter
branch into theSLAMFuse
branch. This task is anticipated to be time-consuming and should be prioritized accordingly. #31 -
Update Docker Files for Algorithms: Update the docker files associated with the algorithms to ensure compatibility and proper functioning within the SLAMFuse environment.
-
Update Documentation for Fuzzing Mechanism: Enhance the existing documentation to reflect the incorporation of the fuzzing mechanism. Ensure that the documentation accurately describes the functionality and usage of the implemented mechanism.
-
Update Dependency List: Review and update the dependency list to reflect any changes resulting from the integration of new features. Ensure that all dependencies are correctly listed and versioned. #29
Timeline:
- All tasks outlined above should be completed by the 1st of June.
- Given the complexity of the merge operation, the initial task of merging the fuzzing mechanism is expected to take the longest and should be prioritized accordingly.
Additional Features Post-June 1st:
-
Provide Docker GPU Support: Following the completion of the initial tasks, the next phase involves providing GPU support within the Docker environment to enhance performance and capability. #32
-
Add Sensor Noise for Lidar and IMU to Fuzzing: Further enhancements will include the addition of sensor noise functionality for Lidar and IMU devices within the fuzzing mechanism, contributing to more comprehensive testing capabilities.