Next Article in Journal
UAVs in Support of Algal Bloom Research: A Review of Current Applications and Future Opportunities
Next Article in Special Issue
Preface: Latest Developments, Methodologies, and Applications Based on UAV Platforms
Previous Article in Journal
Biologically-Inspired Intelligent Flocking Control for Networked Multi-UAS with Uncertain Network Imperfections
Previous Article in Special Issue
Unmanned Aerial Vehicles (UAV) Photogrammetry in the Conservation of Historic Places: Carleton Immersive Media Studio Case Studies
Article Menu
Issue 4 (December) cover image

Export Article

Open AccessArticle
Drones 2018, 2(4), 34; https://doi.org/10.3390/drones2040034

Autonomous Landing of a UAV on a Moving Platform Using Model Predictive Control

Department of Electrical and Computer Engineering, University of Michigan-Dearborn, Dearborn, MI 48128, USA
*
Author to whom correspondence should be addressed.
Received: 9 August 2018 / Revised: 9 October 2018 / Accepted: 10 October 2018 / Published: 12 October 2018
  |  
PDF [2719 KB, uploaded 12 October 2018]
  |  

Abstract

Developing methods for autonomous landing of an unmanned aerial vehicle (UAV) on a mobile platform has been an active area of research over the past decade, as it offers an attractive solution for cases where rapid deployment and recovery of a fleet of UAVs, continuous flight tasks, extended operational ranges, and mobile recharging stations are desired. In this work, we present a new autonomous landing method that can be implemented on micro UAVs that require high-bandwidth feedback control loops for safe landing under various uncertainties and wind disturbances. We present our system architecture, including dynamic modeling of the UAV with a gimbaled camera, implementation of a Kalman filter for optimal localization of the mobile platform, and development of model predictive control (MPC), for guidance of UAVs. We demonstrate autonomous landing with an error of less than 37 cm from the center of a mobile platform traveling at a speed of up to 12 m/s under the condition of noisy measurements and wind disturbances. View Full-Text
Keywords: quadcopter; drone; Kalman filter; vision-based guidance system; autonomous vehicle; unmanned aerial vehicle; model predictive control; aerospace control quadcopter; drone; Kalman filter; vision-based guidance system; autonomous vehicle; unmanned aerial vehicle; model predictive control; aerospace control
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Feng, Y.; Zhang, C.; Baek, S.; Rawashdeh, S.; Mohammadi, A. Autonomous Landing of a UAV on a Moving Platform Using Model Predictive Control. Drones 2018, 2, 34.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Drones EISSN 2504-446X Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top