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Fully autonomous micro air vehicle flight and landing on a moving target using visual–inertial estimation and model‐predictive control
Author(s) -
Tzoumanikas Dimos,
Li Wenbin,
Grimm Marius,
Zhang Ketao,
Kovac Mirko,
Leutenegger Stefan
Publication year - 2019
Publication title -
journal of field robotics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.152
H-Index - 96
eISSN - 1556-4967
pISSN - 1556-4959
DOI - 10.1002/rob.21821
Subject(s) - robotics , micro air vehicle , artificial intelligence , inertial measurement unit , computer science , adaptation (eye) , robot , range (aeronautics) , competition (biology) , real time computing , simulation , computer vision , engineering , aeronautics , aerospace engineering , ecology , physics , optics , aerodynamics , biology
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.