Citation: Chang, C.-W.; Lo, L.-Y.;
Cheung, H.C.; Feng, Y.; Yang, A.-S.;
Wen, C.-Y.; Zhou, W. Proactive
Guidance for Accurate UAV Landing
on a Dynamic Platform: A
Visual–Inertial Approach. Sensors
2022, 22, 404. https://doi.org/
10.3390/s22010404
Academic Editor: Shuanggen Jin
Received: 17 December 2021
Accepted: 1 January 2022
Published: 5 January 2022
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Article
Proactive Guidance for Accurate UAV Landing on a Dynamic
Platform: A Visual–Inertial Approach
Ching-Wei Chang
1
, Li-Yu Lo
2
, Hiu Ching Cheung
1
, Yurong Feng
2
, An-Shik Yang
3
, Chih-Yung Wen
2
and Weifeng Zhou
4,
*
1
Department of Mechanical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong;
chingwei.chang@connect.polyu.hk (C.-W.C.); hiu-ching-athena.cheung@connect.polyu.hk (H.C.C.)
2
Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University,
Kowloon, Hong Kong; liyu.lo@connect.polyu.hk (L.-Y.L.); yurong.feng@connect.polyu.hk (Y.F.);
chihyung.wen@polyu.edu.hk (C.-Y.W.)
3
Department of Energy and Refrigerating Air-Conditioning Engineering,
National Taipei University of Technology, Taipei 10608, Taiwan; asyang@ntut.edu.tw
4
School of Professional Education and Executive Development, The Hong Kong Polytechnic University,
Kowloon, Hong Kong
* Correspondence: chandler.zhou@cpce-polyu.edu.hk; Tel.: +852-3746-0127
Abstract:
This work aimed to develop an autonomous system for unmanned aerial vehicles (UAVs) to
land on moving platforms such as an automobile or a marine vessel, providing a promising solution
for a long-endurance flight operation, a large mission coverage range, and a convenient recharging
ground station. Unlike most state-of-the-art UAV landing frameworks that rely on UAV onboard
computers and sensors, the proposed system fully depends on the computation unit situated on the
ground vehicle/marine vessel to serve as a landing guidance system. Such a novel configuration can
therefore lighten the burden of the UAV, and the computation power of the ground vehicle/marine
vessel can be enhanced. In particular, we exploit a sensor fusion-based algorithm for the guidance
system to perform UAV localization, whilst a control method based upon trajectory optimization
is integrated. Indoor and outdoor experiments are conducted, and the results show that precise
autonomous landing on a 43 cm × 43 cm platform can be performed.
Keywords:
UAV; VTOL; object tracking; deep learning; sensor fusion; kalman filter; autonomous
landing; optimal trajectory
1. Introduction
In recent years, the development and application of unmanned aerial vehicles (UAVs)
have been rapid. For instance, agricultural industries, construction sectors, commercial
delivery corporations, and many others are now eager to adopt aerial robots to boost their
working efficiency [
1
–
3
]. Nevertheless, the payload of a UAV is limited by the fixed capacity
of the battery, and frequent landing operations are required for battery replacement or
recharging. There is hence a significant need for a system for autonomous landing of UAVs
on moving platforms, which would also further increase operation efficiency.
In order to address this issue, this work set out to design a system framework for
a quadrotor UAV to perform landing on unmanned ground vehicles (UGV), a field of
research in which several pioneering works have been published [
4
,
5
]. For instance, DHL’s
AMP Electric Vehicle has been used to test the applicability of UAV pairing with delivery
trucks, where aerial robots deliver parcels that are outside of the main truck delivery route.
During operation, the aerial vehicles are positioned on top of the delivery truck. After
loading, the UAV schedules the route to the delivery point via GPS and take off from the
moving track. Meanwhile, the truck continues its rounds. After a successful delivery, the
UAV flies back to the truck for its next delivery run, where it can also wirelessly recharge
Sensors 2022, 22, 404. https://doi.org/10.3390/s22010404 https://www.mdpi.com/journal/sensors
