estimation module: design and scope (KF/EKF, PID, IMU fusion)
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- Dominant language
- C
- Stars
- 23
- Forks
- 2
- PR merge metrics
- No merged PRs in 30d
Description
Design the estimation module before implementation. Motivated by real sensor-fusion needs seen in production ESP32 deployments (the TERRA platform).
Scope to decide:
- Kalman filter: linear KF and extended KF (EKF), fixed-size state/covariance matrices bounded like the rest of linalg (NUMX_MAX_MAT_ROWS)
- PID controller: standalone, simple, likely the smallest piece
- Quaternion representation and Madgwick/Mahony IMU sensor fusion
Whether this ships as one module or is split (e.g. estimation for KF/EKF, control for PID) is part of this decision, following the same reasoning CONTRIBUTING.md applies to module boundaries elsewhere.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with CONTRIBUTING.md and the existing linalg module boundaries referenced in the issue. Define the scope and organization for KF/EKF, PID, quaternion, and Madgwick/Mahony IMU fusion, including the fixed-size matrix constraints. Done means the module split and implementation scope are documented clearly enough to guide later work.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- c
- Domain
- embedded-iot
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100