Skip to content
WIP: Kalman Filter + visualizations + enclosure
Python C++
Branch: master
Clone or download
Pull request Compare This branch is 1 commit ahead, 3 commits behind JulienMellet:master.
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.


Here is the WIP repo for our Sensor fusion. It basically uses IMU data to improve Lighthouse positioning dynamism. This repo also contains the 3d models of the structure, helpful for the calibration algorithms for example...

There are 3 kinds of files:

  • Data preprocessing: transforms accelerations from IMU and Lighthouses data into 3D points.
  • Sensor fusion: this Kalman Filter (and more variations in progress) estimates the tracker position as well as possible.
  • Visualization: this Blender file uses position calculated after Sensor fusion.


Enclosures options:

  • Main enclosure: 4 arms and 1 body frame.
  • Tetraedron: it allows visibility for at least one diode in any orientation.

Simulation: On the Dev branch, a mini-game simulation is in LH_Simu.blend, see the Python script inside. You can move the blue car with Z, Q, S, D key (Because of french keyboard), and the scanning/calculated position will appear with a green dot.

Calibration: There is also an other way of calculating position from the Lighthouses. It use the assumption that Diodes are on a solid frame (our main enclosure). This Python code allows to know position and orientation of Lighthouses but isn't accurate enough for the moment. A visualization of the calculated points is also in the folder.

You can’t perform that action at this time.