Visual Homing for Micro Aerial Vehicles Using Scene Familiarity

Journal Article (2018)
Author(s)

G.J.J. van Dalen

Kimberly N. McGuire (TU Delft - Control & Simulation)

G. C. H. E. de Croon (TU Delft - Control & Simulation)

Research Group
Control & Simulation
Copyright
© 2018 G.J.J. van Dalen, K.N. McGuire, G.C.H.E. de Croon
DOI related publication
https://doi.org/10.1142/S230138501850005X
More Info
expand_more
Publication Year
2018
Language
English
Copyright
© 2018 G.J.J. van Dalen, K.N. McGuire, G.C.H.E. de Croon
Research Group
Control & Simulation
Issue number
02
Volume number
06
Pages (from-to)
119-130
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

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.

Files

Unmanned_systems_visual.pdf
(pdf | 1.21 Mb)
- Embargo expired in 01-07-2019
License info not available