Autonomous landing on a moving vehicle with an unmanned aerial vehicle

Tomas Baca, Petr Stepan, Vojtech Spurny, Daniel Hert, Robert Penicka, Martin Saska, Justin Thomas, Giuseppe Loianno, Vijay Kumar

Research output: Contribution to journalArticlepeer-review

Abstract

This paper addresses the perception, control, and trajectory planning for an aerial platform to identify and land on a moving car at 15 km/hr. The hexacopter unmanned aerial vehicle (UAV), equipped with onboard sensors and a computer, detects the car using a monocular camera and predicts the car future movement using a nonlinear motion model. While following the car, the UAV lands on its roof, and it attaches itself using magnetic legs. The proposed system is fully autonomous from takeoff to landing. Numerous field tests were conducted throughout the year-long development and preparations for the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2017 competition, for which the system was designed. We propose a novel control system in which a model predictive controller is used in real time to generate a reference trajectory for the UAV, which are then tracked by the nonlinear feedback controller. This combination allows to track predictions of the car motion with minimal position error. The evaluation presents three successful autonomous landings during the MBZIRC 2017, where our system achieved the fastest landing among all competing teams.

Original languageEnglish (US)
Pages (from-to)874-891
Number of pages18
JournalJournal of Field Robotics
Volume36
Issue number5
DOIs
StatePublished - Aug 2019

Keywords

  • aerial robotics
  • control
  • planning
  • position estimation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications

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