About: Navigation, Localization and Stabilization of Formations of Unmanned Aerial and Ground Vehicles     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
rdfs:seeAlso
Description
  • A leader-follower formation driving algorithm developed for control of heterogeneous groups of unmanned micro aerial and ground vehicles stabilized under a top-view relative localization is presented in this paper. The core of the proposed method lies in a novel avoidance function, in which the entire 3D formation is represented by a convex hull projected along a desired path to be followed by the group. Such a representation of the formation provides non-collision trajectories of the robots and respects requirements of the direct visibility between the team members in environment with static as well as dynamic obstacles, which is crucial for the top-view localization. The algorithm is suited for utilization of a simple yet stable visual based navigation of the group (referred to as GeNav), which together with the on-board relative localization enables deployment of large teams of micro-scale robots in environments without any available global localization system. We formulate a novel Model Predictive Control (MPC) based concept that enables to respond to the changing environment and that provides a robust solution with team members' failure tolerance included. The performance of the proposed method is verified by numerical and hardware experiments inspired by reconnaissance and surveillance missions.
  • A leader-follower formation driving algorithm developed for control of heterogeneous groups of unmanned micro aerial and ground vehicles stabilized under a top-view relative localization is presented in this paper. The core of the proposed method lies in a novel avoidance function, in which the entire 3D formation is represented by a convex hull projected along a desired path to be followed by the group. Such a representation of the formation provides non-collision trajectories of the robots and respects requirements of the direct visibility between the team members in environment with static as well as dynamic obstacles, which is crucial for the top-view localization. The algorithm is suited for utilization of a simple yet stable visual based navigation of the group (referred to as GeNav), which together with the on-board relative localization enables deployment of large teams of micro-scale robots in environments without any available global localization system. We formulate a novel Model Predictive Control (MPC) based concept that enables to respond to the changing environment and that provides a robust solution with team members' failure tolerance included. The performance of the proposed method is verified by numerical and hardware experiments inspired by reconnaissance and surveillance missions. (en)
Title
  • Navigation, Localization and Stabilization of Formations of Unmanned Aerial and Ground Vehicles
  • Navigation, Localization and Stabilization of Formations of Unmanned Aerial and Ground Vehicles (en)
skos:prefLabel
  • Navigation, Localization and Stabilization of Formations of Unmanned Aerial and Ground Vehicles
  • Navigation, Localization and Stabilization of Formations of Unmanned Aerial and Ground Vehicles (en)
skos:notation
  • RIV/68407700:21230/13:00206002!RIV14-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(7E08006), P(7E11017), P(GPP103/12/P756), P(LH11053), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 90873
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/13:00206002
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Model Predictive Control; Autonomous Mobile Robots; Compact Formations; Trajectory Planning; Aerial Vehicles (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [37436D33F71A]
http://linked.open...v/mistoKonaniAkce
  • Atlanta
http://linked.open...i/riv/mistoVydani
  • New York
http://linked.open...i/riv/nazevZdroje
  • Proceedings of 2013 International Conference on Unmanned Aircraft Systems
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Krajník, Tomáš
  • Přeučil, Libor
  • Saska, Martin
  • Vonásek, Vojtěch
  • Vaněk, Petr
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000326842400100
http://linked.open.../riv/zahajeniAkce
number of pages
http://bibframe.org/vocab/doi
  • 10.1109/ICUAS.2013.6564767
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 978-1-4799-0817-2
http://localhost/t...ganizacniJednotka
  • 21230
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 77 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software