Reduce noise in raw sensor data by implementing appropriate filtering algorithms to improve measurement accuracy.
- research noise filtering techniques applicable to IMU sensors (low-pass, band-pass, Kalman filters)
- select a suitable algorithm based on sensor data characteristics
- implement chosen filtering techniques and integrate them into the exisitng flow for processing IMU data
- include a test file (look for instructions on Gtest in repo) that is automatically triggered within the build pipeline
Success Criteria:
- quick summary to justify design decisions (which filtering technique was chosen)
- implementation of a filtering function/module
- test that confirm filtered data is smoother and more stable than raw data
- test file is executed as part of build pipeline
Reduce noise in raw sensor data by implementing appropriate filtering algorithms to improve measurement accuracy.
Success Criteria: