Extended Kalman Filter (EKF) implementation and practical considerations. Real-world, real-time implementation and demo on an STM32 microcontroller in C using accelerometer and gyroscope measurements.
Part 4 (final) of sensor fusion video series.
[SUPPORT]
Free trial of Altium Designer: https://www.altium.com/yt/philslab
PCBA from $0 (Free Setup, Free Stencil): https://jlcpcb.com/RHS
Patreon: https://www.patreon.com/phils94
[LINKS]
Git: https://github.com/pms67
Sensor Fusion Part 3: https://youtu.be/hQUkiC5o0JI
Sensor Fusion Part 2: https://youtu.be/BUW2OdAtzBw
Sensor Fusion Part 1: https://youtu.be/RZd6XDx5VXo
IIR Filters: https://youtu.be/QRMe02kzVkA
Tag-Connect SWD Probe: https://www.tag-connect.com/product/tc2030-idc-nl
Small Unmanned Aircraft (Book): https://uavbook.byu.edu/doku.php
Euler Angles: http://control.asu.edu/Classes/MMAE441/Aircraft/441Lecture9.pdf (from slide 17)
[TIMESTAMPS]
00:00 Introduction
00:21 Altium Designer Free Trial
00:44 JLCPCB and Design Files
01:06 Pre-Requisites
01:53 'Low-Level' Firmware Overview
07:00 Axis Re-Mapping
08:17 Calibration
09:42 Filtering Raw Measurements
12:12 EKF Algorithm Overview
14:11 EKF Initialisation
17:12 EKF Predict Step
19:26 Matlab/Octave Symbolic Toolbox
21:11 EKF Update Step
22:16 Setting EKF Parameters
23:26 Debug Set-up and Tag-Connect SWD Probe
24:05 Live Demonstration
26:29 Practical Considerations
ID: QIBvbJtYjWuHiTG0uCoK