Open Issues Need Help
View All on GitHubAI Summary: Update the project's build workflow (.github/workflows/build.yml) to use the `make coverage` target instead of CMake's coverage target once a new Docker Engine version resolves a bug that prevents the `Makefile`'s coverage target from executing properly. This involves monitoring the resolution of a Moby issue and a Github Runner update.
AI Summary: Revert two lines of code (82-83) in the `.github/workflows/build.yml` file of the FOUND project's GitHub repository, restoring the use of the `erclu/check-crlf` action for CI/CD. Consider removing the `.gitattributes` file if it's solely for line ending enforcement, or keeping it as a secondary check. This is in response to a pull request that has been merged into `erclu/check-crlf`.
AI Summary: Implement a Richardson Image Gradient Edge Detection Algorithm (RIGEDA) for the FOUND satellite navigation system. This involves calculating the magnitude of the image gradient using the Richardson approximation (as detailed in the provided paper), selecting the highest gradient values based on a configurable hyperparameter, and integrating this algorithm into the existing FOUND system's edge detection module.
AI Summary: Implement an Ellipsoid Distance Determination Algorithm (EDDA) for a satellite navigation system. This involves using equations from a research paper to calculate a satellite's position relative to Earth, assuming an ellipsoid Earth model. The algorithm will leverage existing matrix algebra and rotation functions, but requires implementing a solution for a specific equation (either iterative or least-squares) and incorporating Greenwich Mean Sidereal Time for Earth's Principal Axis Frame transformation.
AI Summary: Implement a Boxed Edge Filtering Algorithm (BEFA) for outlier elimination in the FOUND satellite navigation system. This involves adapting a box-based outlier elimination technique described in a linked research paper (specifically pages 10-11) to improve the accuracy of edge detection in images used for distance determination. The implementation can optionally omit the eigenvalue criterion for simplification. Combining this with a previously implemented feature (#23) is suggested for easier integration.
AI Summary: Create an abstract base class `EdgeFilteringAlgorithm` for image processing in the FOUND satellite navigation system. This class should be integrated into the `DistanceExecutor` workflow, allowing for multiple edge filtering algorithms to be used concurrently. The implementation should involve creating appropriate flags for algorithm selection, a provider method to manage enabled algorithms, and modifying the `DistanceExecutor` constructor and factory method to accommodate the list of algorithms.
AI Summary: The task is to modify the regular expressions in the C++ unit tests (`executors-test.cpp` and `integration-test.cpp`) of the FOUND project. Specifically, the regex matching floating-point numbers needs to be updated to correctly handle scientific notation and different architectures, ensuring consistent test results across various systems. The goal is to replace hardcoded floating-point values in the expected output regex with a more flexible pattern that matches any floating-point number in scientific notation.