Vision based autonomous landing of an Unmanned Aerial Vehicle on a stationary target

Vidya Sudevan, Amit Shukla, Hamad Karki

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

28 Scopus citations

Abstract

The foremost, yet challenging problem of an Unmanned Aerial Vehicle (UAV) is the autonomous landing. This paper presents a solution for the independent landing of a quadrotor UAV on a stationary target. This method includes a searching and a landing part. The visual data is collected by the onboard camera of the AR Drone. Speeded Up Robust Features (SURF) method is used to detect and compute the keypoint descriptors and Fast Approximate Nearest Neighbor Search Library (FLANN) based descriptor matcher is utilized for the accurate matching of the template image with the captured images to determine the target position. The aim of this method is to minimize the distance between the drone and the target. A Proportional-Integral-Derivative (PID) controller is designed to generate the desired velocity signals for the drone. Also, in this work, the drone is directly navigating and landing on the target by adjusting the x, y and z velocities simultaneously. The method is tested and validated on a quadrotor with two different initial heights.

Original languageBritish English
Title of host publicationICCAS 2017 - 2017 17th International Conference on Control, Automation and Systems - Proceedings
PublisherIEEE Computer Society
Pages362-367
Number of pages6
ISBN (Electronic)9788993215137
DOIs
StatePublished - 13 Dec 2017
Event17th International Conference on Control, Automation and Systems, ICCAS 2017 - Jeju, Korea, Republic of
Duration: 18 Oct 201721 Oct 2017

Publication series

NameInternational Conference on Control, Automation and Systems
Volume2017-October
ISSN (Print)1598-7833

Conference

Conference17th International Conference on Control, Automation and Systems, ICCAS 2017
Country/TerritoryKorea, Republic of
CityJeju
Period18/10/1721/10/17

Keywords

  • Autonomous Landing
  • Feature detection and matching
  • PID Controller
  • SURF
  • UAV

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