Measuring dynamic tilt with an inertial measurement unit

Why would you want to know the dynamic tilt angle on a vehicle?

Consider a classic example of a plane in the clouds. The pilot cannot see the ground, nor can he or she trust their instincts because they will feel a false gravity when the aircraft is turning. This means they need a dynamic tilt sensor which – in an aircraft – is often called a vertical gyro or the artificial horizon. Similar technology is used in automobiles.



With cars getting smarter, and evolving to autonomous navigation, there is a real need for accurate dynamic orientation data of the vehicle.

Orientation is just another way of saying dynamic tilt and heading

In this a ACEINNA video – How to measure dynamic Tilt and orientation with an IMU – you will learn how to integrate an IMU for Dynamic Tilt and Orientation Measurement.

The Algorithms must combine both Acceleration and Angular Rate Measurement. Using an Extended Kalman Filter is a good way to use acceleration to smoothly correct drift of angular rate measurement and also provide an absolute reference.

“OpenIMUTM is a first of its kind professionally supported, open-source GPS/GNSS-aided inertial navigation software stack for low-cost precise navigation applications,” explains Mike Horton, CTO of ACEINNA. “OpenIMU enables advanced, easy-to-deploy localisation and navigation algorithm solutions for a fraction of the time and cost of traditional methods. “OpenIMU’s combination of open-source software and low-cost hardware enables rapid development of advanced solutions for drones, robotics, and autonomous applications.”

The OpenIMU Development hardware development kit includes JTAG-pod, precision mount fixture, EVB, and an OpenIMU300 module. The OpenIMU module features ACEINNA’s 5 deg/Hr, 9-Axis gyro, accelerometer, and magnetometer sensor suite with an onboard 180MHz ARM Coretex floating-point CPU.

The IMU is delivered in a small (24x37x9.5mm), easy to integrate module that operates from 2.7-5.5VDC.

This freely downloadable stack includes:

* FreeRTOS-based data collection and sampling engine

* Performance-tuned, real-time, navigation-grade GPS/INS Kalman Filter
library

* Free IDE/compiler tool chain based on Visual Studio Code

* JTAG debugging for debugging code loaded on IMU

* Data logging, graphing, Allen Variance plots, and maps,

* Extensive documentation

* Robust simulation environment with advanced sensor error models.