Self-Localization of Unmanned Aerial Vehicles Based on Optical Flow in Inboard Camera Image

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00316982" target="_blank" >RIV/68407700:21230/18:00316982 - isvavai.cz</a>

Result on the web

<a href="https://link.springer.com/book/10.1007%2F978-3-319-76072-8" target="_blank" >https://link.springer.com/book/10.1007%2F978-3-319-76072-8</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-76072-8_8" target="_blank" >10.1007/978-3-319-76072-8_8</a>

Result language

angličtina

Original language name

Self-Localization of Unmanned Aerial Vehicles Based on Optical Flow in Inboard Camera Image

Original language description

This paper proposes and evaluates the implementation of a self-localization system intended for use in Unmanned Aerial Vehicles. Accurate localization is necessary for UAVs for efficient stabilization, navigation and collision avoidance. Conventionally, this requirement is fulfilled using external hardware infrastructure, such as Global Navigation Satellite System or visual motion-capture system. These approaches are, however, not applicable in environments where deployment of cumbersome motion capture equipment is not feasible, as well as in GNSS-denied environments. Systems based on Simultaneous Localization and Mapping (SLAM) require heavy and expensive onboard equipment and high amounts of data transmissions for sharing maps between UAVs. Availability of a system without these drawbacks is crucial for deployment of tight formations of multiple fully autonomous micro UAVs for both outdoor and indoor missions. The project was inspired by the often used sensor PX4FLOW Smart Camera. The aim was to develop a similar sensor, without the drawbacks observed in its use, as well as to make the operation of it more transparent and to make it independent of a specific hardware. Our proposed solution requires only a lightweight camera and a single-point range sensor. It is based on optical flow estimation from consecutive images obtained from downward-facing camera, coupled with a specialized RANSAC-inspired post-processing method that takes into account flight dynamics. This filtering makes it more robust against imperfect lighting, homogenous ground patches, random close objects and spurious errors. These features make this approach suitable even for coordinated flights through demanding forest-like environment. The system is designed mainly for horizontal velocity estimation, but specialized modifications were also made for vertical speed and yaw rotation rate estimation. These methods were tested in a simulator and subsequently in real-world conditions.

Czech name

—

Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

20204 - Robotics and automatic control

Project

<a href="/en/project/GA16-24206S" target="_blank" >GA16-24206S: Efficient Information Gathering with Dubins Vehicles in Persistent Monitoring and Surveillance Missions</a><br>

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2018

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Modelling and Simulation for Autonomous Systems (MESAS 2017)

ISBN

978-3-319-76071-1

ISSN

0302-9743

e-ISSN

—

Number of pages

27

Pages from-to

106-132

Publisher name

Springer International Publishing AG

Place of publication

Cham

Event location

Řím

Event date

Oct 24, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000444831600008