- saves a small amount of work for the ekf2 selector in multi-EKF mode (visual_odometry_aligned now ignored)
- helps to distinguish the origin/purpose from vehicle_odometry and vehicle_visual_odometry
- ekf2 can now run in multi-instance mode (currently up to 9 instances)
- in multi mode all estimates are published to alternate topics (eg estimator_attitude instead of vehicle_attitude)
- new ekf2 selector runs in multi-instance mode to monitor and compare all instances, selecting a primary (eg N x estimator_attitude => vehicle_attitude)
- sensors module accel & gyro inconsistency checks are now relative to the mean of all instances, rather than the current primary (when active ekf2 selector is responsible for choosing primary accel & gyro)
- existing consumers of estimator_status must check estimator_selector_status to select current primary instance status
- ekf2 single instance mode is still fully supported and the default
Co-authored-by: Paul Riseborough <gncsolns@gmail.com>
- new sensors work item that subscribes to N x sensor_gps and publishes vehicle_gps_position
- blending is now configurable with SENS_GPS_MASK and SENS_GPS_TAU
Co-authored-by: Jacob Crabill <jacob@volans-i.com>
Co-authored-by: Jacob Dahl <dahl.jakejacob@gmail.com>
120 seconds of learning time in 3D fusion mode was too long for most normal flights. The learned bias is usually really good after a shorter period and was not used to update the parameters. 30s seems to be a good compromise.
Daniel Agar