Measuring dynamic tilt with an IMU

20th December 2018
Posted By : Alex Lynn
Measuring dynamic tilt with an IMU

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 new ACEINNA video, 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.

“OpenIMU is a first of its kind professionally supported, open-source GPS/GNSS-aided inertial navigation software stack for low-cost precise navigation applications,” explained 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.

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