Citation: Pokorný, M.; Nowaková, J.;
Doˇcekal, T. Adaptive Ascent Control
of a Collaborative Object
Transportation System Using Two
Quadrotors. Sensors 2022, 22, 2923.
https://doi.org/10.3390/s22082923
Academic Editor: Sergio Toral Marín
Received: 28 February 2022
Accepted: 7 April 2022
Published: 11 April 2022
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Article
Adaptive Ascent Control of a Collaborative Object Transportation
System Using Two Quadrotors
Miroslav Pokorný
1,
*, Jana Nowaková
2
and Tomáš Doˇcekal
1
1
Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer
Science, VSB-Technical University of Ostrava, 17. listopadu 2172/15, 708 33 Ostrava-Poruba, Czech Republic;
tomas.docekal@vsb.cz
2
Department of Computer Science, Faculty of Electrical Engineering and Computer Science, VSB-Technical
University of Ostrava, 17. listopadu 2172/15, 708 33 Ostrava-Poruba, Czech Republic; jana.nowakova@vsb.cz
* Correspondence: miroslav.pokorny@vsb.cz
Abstract:
The paper focuses on the issue of collaborative control of a two quadrotor (Unmanned Aerial
Vehicle QDR) system. In particular, two quadrotors perform the task of horizontally transporting a
long payload along a predefined trajectory. A leader–follower method is used to synchronize the
motion of both QDRs. Conventional PD controllers drive the motion of the leader QDR-L to follow a
predefined trajectory. To control a follower QDR-F drive, in the case of indoor applications, a Position
Feedback Controller approach (PFC) can be used. To control the QDR-F, the PFC system uses the
position information of QDR-L and the required accurate tracking cameras. In our solution, outdoor
applications are considered, and usage of the Global Positioning System (GPS) is needed. However,
GPS errors can adversely affect the system’s stability. The Force Feedback Controller approach (FFC)
is therefore implemented to control the QDR-F motion. The FFC system assumes a rigid gripping of
payload by both QDRs. The QDR-F collaborative motion is controlled using the feedback contact
forces and torques acting on it due to the motion of the QDR-L. For FFC implementation, the principle
of admittance control is used. The admittance controller simulates a virtual “mass-spring-damper”
system and drives the motion of the QDR-F according to the contact forces. With the FFC control
scheme, the follower QDR-F can be controlled without using the QDR-L positional feedback and the
GPS. The contribution to the quality of payload transportation is the novelty of the article. In practice,
one of the requirements may be to maintain the horizontal position of the payload. In this paper, an
original solution is presented to minimize the horizontal position difference of both QDRs. A new
procedure of the transfer admittance controller adaptation according to the mass of the transported
payload is designed. The adaptive admittance FFC system is implemented in a Matlab-Simulink
environment. The effectiveness of its trajectory tracking and horizontal stabilization functions for
variations of the payload mass are demonstrated by numerical calculations.
Keywords:
unmanned aerial vehicles; collaborative transportation; admittance force feedback control;
adaptation
1. Introduction
The development of modern methods and tools of mechatronics is accompanied by a
wide development of robot applications in many fields of production and services. Special
attention is paid to quadrotors (QDRs), which are used for package delivery [
1
], wildfire
monitoring, and fighting [
2
], search and rescue operations [
3
–
5
], disaster management [
6
]
and military activities (MQ1 Predator, Orion, UNITED 40) [
7
], for example. The use of
QDRs in the implementation of such activities brings a significant increase in their efficiency.
However, the use of individual drones is limited by the size and mass of payload
transported. Therefore, it is very often necessary to use more cooperating drones to perform
tasks in a real environment. The performance of drones can be significantly enhanced by
Sensors 2022, 22, 2923. https://doi.org/10.3390/s22082923 https://www.mdpi.com/journal/sensors
