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Paul Riseborough 470098e182 EKF: update default tuning parameters 
Parameters needed to be changed when covariance prediction error was corrected.
The magnetic earth and body field process noise now use separate parameters to help with tuning
2016-04-05 22:23:37 +02:00
attitude_fw
Removed spurious print in wheel controller
2016-03-12 11:23:08 +01:00
EKF
EKF: update default tuning parameters
2016-04-05 22:23:37 +02:00
l1
initialize ECL_L1 variables
2016-03-03 11:22:07 +01:00
matlab
EKF: Fix scaling error in covariance prediction derivation
2016-04-05 22:23:37 +02:00
matrix @ 95e3d7d6ce
add matrix submodule
2016-02-17 17:38:21 -08:00
validation
Add vibration magnitude estimation
2016-02-25 16:54:24 +01:00
.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
EKF: add travis build
2016-02-17 18:51:40 -08:00
build.sh
EKF: add comments and licensing information to builder files
2016-02-17 19:55:47 -08:00
CMakeLists.txt
added function for fusing airspeed
2016-03-30 17:01:03 +02:00
ecl.h
Initial import
2015-10-26 16:06:30 +01:00
LICENSE
Initial commit
2015-10-26 15:41:25 +01:00
README.md
Add travis build check badge
2016-02-22 23:49:58 -08:00

README.md

ECL

Very lightweight Estimation & Control Library.

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 currently BSD licensed, but might move to Apache 2.0.

Building EKF Library

Prerequisite:

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