Abstract
Autonomous navigation is a major challenge in the development of Micro Aerial Vehicles (MAVs). Especially, when an algorithm has to be efficient, insect intelligence can be a source of inspiration. One of the elementary navigation tasks of insects and robots is “homing”, which is the task of returning to an initial starting position. A promising approach uses learned visual familiarity of a route to determine reference headings during homing. In this paper, an existing biological proof-of-concept is transferred to an algorithm for micro drones, using vision-in-the-loop experiments in indoor environments. An artificial neural network determines which control actions to take place.
Original language | English |
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Pages (from-to) | 119-130 |
Journal | Unmanned Systems |
Volume | 06 |
Issue number | 02 |
DOIs | |
Publication status | Published - 8 Jun 2018 |
Keywords
- Visual Homing
- Scene familiarity
- MAV