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T

Paul Riseborough 9c31632e2b EKF: Add parameter control of individual IMU axis delta velocity bias estimation

Add a bitmask parameter to control bias learning for individual axes. This is achieved by setting the disabled states to zero together with their corresponding covariances.
Minor cleanup of the covariance prediction comments.
Removal of unnecessary variable copy operations.
Replace index operations to initialise covariance to zero with the more efficient memset.

2017-05-11 07:51:37 +02:00

attitude_fw

Removed obsolete fields from ECL control data

2017-02-12 11:40:14 +01:00

EKF

EKF: Add parameter control of individual IMU axis delta velocity bias estimation

2017-05-11 07:51:37 +02:00

clang-tidy modernize-redundant-void-arg

2017-01-14 16:24:45 -08:00

matlab

EKF: Clean up auto-code files for body frame velocity measurements

2017-03-06 09:01:46 +11:00

matrix @ cf924956d7

cmake add all EKF sources (#243 )

2017-02-27 00:46:48 -05:00

validation

c++11 initialization cleanup (#237 )

2017-02-05 13:05:10 -05:00

.gitignore

ignore build directory

2016-02-17 17:34:28 -08:00

.gitmodules

add matrix submodule

2016-02-17 17:38:21 -08:00

.travis.yml

cmake add all EKF sources (#243 )

2017-02-27 00:46:48 -05:00

build.sh

cmake add all EKF sources (#243 )

2017-02-27 00:46:48 -05:00

CMakeLists.txt

EKF: Add multi-rotor drag model for wind estimation

2017-04-16 13:07:12 +02:00

CONTRIBUTING.md

Create CONTRIBUTING.md

2016-05-19 18:14:33 +10:00

ecl.h

ecl.h: guard PX4 defines with ifdef

2016-06-02 16:29:55 +01:00

LICENSE

Initial commit

2015-10-26 15:41:25 +01:00

README.md

Update README.md

2016-10-08 11:00:52 +02:00

README.md

ECL

Very lightweight Estimation & Control Library.

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.

Building EKF Library

Prerequisites:

Matrix: A lightweight, BSD-licensed matrix math library: https://github.com/px4/matrix - it is automatically included as submodule.

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