(Sponsored) Accelerometers and Gyroscopes - Sensor Fusion #1 - Phil's Lab #33

Phil explains the fundamentals of accelerometers and gyroscopes and demonstrates how to combine their data for attitude estimation on an STM32.

Part 1 of sensor fusion video series showing the need for combining sensor data, for example, to estimate the attitude of an aircraft (e.g. UAV) using an inertial measurement unit (IMU). Benefits and problems of typical sensors, such as accelerometers and gyroscopes. Real-world, practical considerations and demonstrations on a real-time embedded system (STM32-based, using the C language). Future videos will cover complementary filters and extended Kalman filters. (AD: This video includes a paid promotion for JLCPCB and Altium.) Free trial of Altium Designer: altium.com/yt/philslab (AD) Visit jlcpcb.com/RHS for $2 for five 2-layer PCBs and $5 for five 4-layer PCBs. (AD) Patreon: patreon.com/phils94 Git: github.com/pms67 Serial Oscilloscope: x-io.co.uk/serial-oscilloscope/ Euler Angles: control.asu.edu/Classes/MMAE441/Aircraft/441Lecture9.pdf (from slide 17) [TIMESTAMPS] 00:00 Introduction 00:14 JLCPCB and Git Repo (Ad) 00:40 Altium Designer Free Trial (Ad) 01:08 Video Overview 01:44 Why Sensor Fusion? 02:23 Example: Aircraft Attitude Estimation 03:29 Euler Angles 04:27 Accelerometer 07:18 Implementation: Accelerometer Attitude Estimation 09:48 Gyroscope 11:54 Implementation: Gyroscope Attitude Estimation 13:48 Conclusions ID: QIBvbJtYjWuHiTG0uCoK