Vision-based autonomous flocking of UAVs in unknown forest environment

Fang Liao, Jianliang Wang, Rodney Teo, Yuchao Hu, Shupeng Lai, Jinqiang Cui, Feng Lin

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

This paper studies tandem flocking of a team of unmanned aerial vehicles (UAVs) equipped with limited range sensors exploring an obstacle-rich GPS-denied environment such as a forest or urban canyon. There is no communication between UAVs and the follower can only estimate its leader's relative position by its on-board camera. A vision-based leader-follower flocking strategy is proposed to achieve this kind of flocking in unknown cluttered environments. The leader UAV explores its way to reach a given goal position and the follower UAV follows its corresponding leader UAV via on-board camera and avoid obstacles at the same time. The simulation of a team of six UAVs demonstrates the effectiveness of our proposed flocking strategy in a forest environment.

Original languageEnglish
Title of host publication12th IEEE International Conference on Control and Automation, ICCA 2016
PublisherIEEE Computer Society
Pages892-897
Number of pages6
ISBN (Electronic)9781509017386
DOIs
Publication statusPublished - 7 Jul 2016
Externally publishedYes
Event12th IEEE International Conference on Control and Automation, ICCA 2016 - Kathmandu, Nepal
Duration: 1 Jun 20163 Jun 2016

Publication series

NameIEEE International Conference on Control and Automation, ICCA
Volume2016-July
ISSN (Print)1948-3449
ISSN (Electronic)1948-3457

Conference

Conference12th IEEE International Conference on Control and Automation, ICCA 2016
Country/TerritoryNepal
CityKathmandu
Period1/06/163/06/16

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering

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