Fully autonomous micro air vehicle flight and landing on a moving target using visual–inertial estimation and model‐predictive control

Dimos Tzoumanikas, Wenbin Li, Marius Grimm, Ketao Zhang, Mirko Kovac, Stefan Leutenegger

Research output: Contribution to journalArticle

Abstract

The Mohamed Bin Zayed International Robotics Challenge (MBZIRC) held in spring 2017 was a very successful competition well attended by teams from all over the world. One of the challenges (Challenge 1) required an aerial robot to detect, follow, and land on a moving target in a fully autonomous fashion. In this paper, we present the hardware components of the micro air vehicle (MAV) we built with off the self components alongside the designed algorithms that were developed for the purposes of the competition. We tackle the challenge of landing on a moving target by adopting a generic approach, rather than following one that is tailored to the MBZIRC Challenge 1 setup, enabling easy adaptation to a wider range of applications and targets, even indoors, since we do not rely on availability of global positioning system. We evaluate our system in an uncontrolled outdoor environment where our MAV successfully and consistently lands on a target moving at a speed of up to 5.0 m/s.
Original languageEnglish
JournalJournal of Field Robotics
Early online date27 Oct 2018
DOIs
Publication statusE-pub ahead of print - 27 Oct 2018

Keywords

  • autonomous landing
  • micro aerial vehicles
  • model based control
  • visual-inertial estimation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications

Cite this

Fully autonomous micro air vehicle flight and landing on a moving target using visual–inertial estimation and model‐predictive control. / Tzoumanikas, Dimos; Li, Wenbin; Grimm, Marius; Zhang, Ketao; Kovac, Mirko; Leutenegger, Stefan.

In: Journal of Field Robotics, 27.10.2018.

Research output: Contribution to journalArticle

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