Combining Cameras, Magnetometers and Machine-Learning into a Close-Range Localization System for Docking and Homing
Marc Hildebrandt, Leif Christensen, Frank Kirchner
In MTS/IEEE Oceans 2017 Anchorage, (OCEANS-2017), 18.9.-21.9.2017, Anchorage, Alaska, IEEE, Sep/2017.
In this work we are describing a multi-modal short-
range navigation system for precision positioning tasks such
as docking of a robotic vehicle in 3d space. The two input
modalities, a monocular camera tracking a visual marker and an
array of 3-axis magnetometers tracking a magnet, were chosen
to cover a wide range of environmental conditions in order to
increase the versatility and robustness of the navigation system.
A comprehensive analysis of the individual components of the
system is provided, resulting in a reliable estimate of its real-