Daniel Agar cebdc3d829 ekf run output predictor immediately with new IMU data (#471)
* EKF collect_imu take const imu sample and populate buffer

* EKF calculateOutputStates cleanup

* EKF add calculate_quaternion output predictor method

* EKF: update documentation

* EKF: remove unnecessary getter function

* EKF calculateOutputStates only apply dt correction to bias

* EKF pytest assert attitude validity, not update() return

* EKF: correct documentation

* EKF: Do not make attitude validity dependent on yaw alignment status

Yaw alignment could fail in flight due to temporary loss of data and yet the quaternions would still usable for stabilisation even though the absolute earth yaw angle wrt true north was uncertain.
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ECL

Very lightweight Estimation & Control Library.

DOI Build Status

This library solves the estimation & control problems of a number of robots and drones. It accepts GPS, vision and inertial sensor inputs. It is extremely lightweight and efficient and yet has the rugged field-proven performance.

The library is BSD 3-clause licensed.

EKF Documentation

Building EKF

Prerequisites:

By following the steps mentioned below you can create a shared library which can be included in projects using -l flag of gcc:

mkdir Build/
cd Build/
cmake ../EKF
make

Alternatively, just run:

./build.sh
Description
a mirror of official PX4-Autopilot
Readme BSD-3-Clause 587 MiB
Languages
C++ 51.2%
C 38.5%
CMake 4.7%
Python 3.9%
Shell 1.3%
Other 0.1%