Visual Homing for Micro Aerial Vehicles using Scene Familiarity

Gerald van Dalen, Kimberly Mcguire, Guido de Croon

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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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. An elementary navigation task is homing, which means autonomously returning to the initial location. 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.
Original languageEnglish
Title of host publicationInternational Micro Air Vechicle Competition and Conference 2016
Subtitle of host publicationBeijing, China
EditorsZhihong Peng, Feng Lin
Pages307-313
Publication statusPublished - 2016
EventInternational Micro Air Vechicle Competition and Conference 2016 - Beijing, China
Duration: 17 Oct 201621 Oct 2016
http://www.imavs.org/2016/

Conference

ConferenceInternational Micro Air Vechicle Competition and Conference 2016
Abbreviated titleIMAV2016
CountryChina
CityBeijing
Period17/10/1621/10/16
Internet address

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