Assignment Sensor fusion with GPS and IMU

This INDIVIDUAL assignment is described in this document Localisation2020.pdf Download Localisation2020.pdf

Make sure to take a look at the self-study materal on Algorithms before you start the assignment.

To help everyone get started and to encourage collaboration there is an initial group assignment Questions on GPS and IMU assignment to be completed in the same groups as the Object detection assignment.

It is easiest solved in Matlab, where these files Download these files are available for download, however you can also use Octave, Python, Julia, or any other tool of your choice, but you will then need to convert the provided code yourself.

The problem describes how to use sensor fusion by a Kalman filter to do positioning by combining sensor information from a GPS and an IMU (accelerometer and gyro). You will use prerecorded real world data and study the performance in a situation with GPS outage. You will get some experience of tuning a sensor fusion filter in a real situation. You will also study the performance improvement achievable by using an improved motion model and an additional speedometer sensor.

Optional material: To really understand the dynamical model and transformations used in the assignment you might want to have a look at

• how quaternions or rotational matrices are used to describe rotations Links to an external site.
• another nice video with further explanation Links to an external site.
• or alternatively this open-gl tutorial about rotations Links to an external site.
• An experiment showing why you might prefer quaternions Links to an external site. (video 2min)

but you will be able to do the exercise without looking at this.

Upload a presentation with text and figures illustrating your solutions before the deadline. Also upload your code.  The solution will be peer reviewed by your colleagues.

Make up assignment (associated with being late on this assignment): Add to your presentation specified above with a presentation about quaternions (see optional material) to show that you understand the basics.

Note that you will also need to do a peer-review of the presentation of one of your colleagues.