Repository navigation
Conversation
Preserve observation rows for all-landmark measurements and explicit pose batches, including singleton maps and singleton batches. Retain scalar explicit-landmark vectors and add analytic native sensor/reading/EKF regressions. AI assistance: OpenAI Codex (gpt-6.1-sol).
Up to standards ✅🟢 Issues
|
| Metric | Results |
|---|---|
| Complexity | 11 |
| Duplication | 0 |
NEW Get contextual insights on your PRs based on Codacy's metrics, along with PR and Jira context, without leaving GitHub. Enable AI reviewer
TIP This summary will be updated as you push new changes.
This branch has not been deployed
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Summary
RangeBearingSensor.h()currently squeezes any single observation row into a vector. With a one-landmark map,visible()then enumerates range and bearing as two separate features. Range/angle filtering raises a scalar indexing error, and EKF can receive the nonexistent landmark ID 1. An explicit batch containing one vehicle pose also loses its row axis.Preserve observation rows when requesting all landmarks or a pose batch. Keep the existing two-element vector for an explicit landmark and a scalar vehicle pose. Add modern type hints, clarify these shapes, and test analytic observations, range/angle visibility, reading IDs, empty/multiple controls, and real one-landmark mapping/SLAM.
Validation
968ed048639c01c9032e256565731e2703de77fe.git diff --checkpass. The existing sensor source reports the same 9 lint diagnostics on the base and the patch, with no additions.Checklist
pytest), with the existing skips listed aboveAI assistance: prepared with OpenAI Codex (
gpt-6.1-sol). The validation above was executed in the native environment.