Abstract

This article presents the design and development of Scissorbot, a novel mid-flight reconfigurable geometry quadcopter that reduces its lateral-span using a single servomotor coupled with a compact bevel differential gearbox. Scissorbot possesses unique practical features, including geometrical symmetricity, fault tolerance to the servomotor, and the gearbox’s weight-scalability. Scissorbot achieves significant lateral-span reduction without the risk of propeller tip collision by positioning adjacent propellers in different planes. To the best of author’s knowledge, the maximum lateral-span reduction surpasses any controllable morphing quadcopter reported in the literature. This work derives a detailed attitude dynamics model and conducts a theoretical analysis of the gearbox. The attitude control is accomplished through the implementation of a robust controller, which exhibits exponential tracking, even in the presence of parametric uncertainties, and propeller aerodynamics disturbances. A velocity controller augments the attitude controller. The control allocation loop is parametrized to adapt to the reconfiguration process. Various evaluations, encompassing multibody simulations and hardware flight experiments, assess Scissorbot’s performance. The results unequivocally demonstrate controller’s excellent tracking in simulations and on the hardware prototype across all scenarios. Moreover, the experiments validate the fault tolerance feature of Scissorbot. In addition, a comprehensive study is performed to analyze the scalability of the current gearbox for higher-weight Scissorbot prototypes.

References

1.
Nekoo
,
S. R.
,
Ángel Acosta
,
J.
,
Heredia
,
G.
, and
Ollero
,
A.
,
2021
, “
A Benchmark Mechatronics Platform to Assess the Inspection Around Pipes With Variable Pitch Quadrotor for Industrial Sites
,”
Mechatronics
,
79
(
1
), p.
102641
.
2.
Li
,
H.
,
Savkin
,
A. V.
, and
Vucetic
,
B.
,
2020
, “
Autonomous Area Exploration and Mapping in Underground Mine Environments by Unmanned Aerial Vehicles
,”
Robotica
,
38
(
3
), pp.
442
456
.
3.
Senthilnath
,
J.
,
Kumar
,
A.
,
Jain
,
A.
,
Harikumar
,
K.
,
Thapa
,
M.
,
Suresh
,
S.
,
Anand
,
G.
, and
Benediktsson
,
J. A.
,
2022
, “
BS-McL: Bilevel Segmentation Framework With Metacognitive Learning for Detection of the Power Lines in UAV Imagery
,”
IEEE. Trans. Geosci. Remote. Sens.
,
60
(
1
), pp.
1
12
.
4.
Lee
,
J. Y. S.
,
Leang
,
K. K.
, and
Yim
,
W.
,
2018
, “
Design and Control of a Fully-Actuated Hexrotor for Aerial Manipulation Applications
,”
ASME J. Mech. Rob.
,
10
(
4
), p.
041007
.
5.
McArthur
,
D. R.
,
Chowdhury
,
A. B.
, and
Cappelleri
,
D. J.
,
2018
, “
Design of the Interacting-BoomCopter Unmanned Aerial Vehicle for Remote Sensor Mounting
,”
ASME J. Mech. Rob.
,
10
(
2
), p.
025001
.
6.
Falanga
,
D.
,
Kleber
,
K.
,
Mintchev
,
S.
,
Floreano
,
D.
, and
Scaramuzza
,
D.
,
2018
, “
The Foldable Drone: A Morphing Quadrotor That Can Squeeze and Fly
,”
IEEE Rob. Autom. Lett.
,
4
(
2
), pp.
209
216
.
7.
Fabris
,
A.
,
Kleber
,
K.
,
Falanga
,
D.
, and
Scaramuzza
,
D.
,
2021
, “
Geometry-Aware Compensation Scheme for Morphing Drones
,”
IEEE International Conference on Robotics and Automation (ICRA)
,
Xi'an, China
,
June 5
, IEEE, pp.
592
598
.
8.
Zhao
,
N.
,
Luo
,
Y.
,
Deng
,
H.
, and
Shen
,
Y.
,
2017
, “
The Deformable Quad-Rotor: Design, Kinematics and Dynamics Characterization, and Flight Performance Validation
,”
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
,
Vancouver, Canada
,
Sept. 24
, pp.
2391
2396
.
9.
Yang
,
T.
,
Zhang
,
Y.
,
Li
,
P.
,
Shen
,
Y.
,
Liu
,
Y.
, and
Chen
,
H.
,
2020
, “
SNIAE-SSE Deformation Mechanism Enabled Scalable Multicopter: Design, Modeling and Flight Performance Validation
,”
IEEE International Conference on Robotics and Automation (ICRA)
,
Virtual
,
May 31–Aug. 31
, IEEE, pp.
864
870
.
10.
Hu
,
D.
,
Pei
,
Z.
,
Shi
,
J.
, and
Tang
,
Z.
,
2021
, “
Design, Modeling and Control of a Novel Morphing Quadrotor
,”
IEEE Rob. Autom. Lett.
,
6
(
4
), pp.
8013
8020
.
11.
Riviere
,
V.
,
Manecy
,
A.
, and
Viollet
,
S.
,
2018
, “
Agile Robotic Fliers: A Morphing-Based Approach
,”
Soft Rob.
,
5
(
5
), pp.
541
553
.
12.
Kumar
,
R.
,
Deshpande
,
A. M.
,
Wells
,
J. Z.
, and
Kumar
,
M.
,
2020
, “
Flight Control of Sliding Arm Quadcopter With Dynamic Structural Parameters
,”
International Conference on Intelligent Robots and Systems (IROS)
,
Las Vegas, NV
,
Oct. 25–29
, IEEE, pp.
1358
1363
.
13.
Patnaik
,
K.
,
Mishra
,
S.
,
Sorkhabadi
,
S. M. R.
, and
Zhang
,
W.
,
2020
, “
Design and Control of Squeeze: A Spring-Augmented Quadrotor for Interactions With the Environment to Squeeze-and-Fly
,”
International Conference on Intelligent Robots and Systems (IROS)
,
Las Vegas, NV
,
Oct. 25–29
, IEEE, pp.
1364
1370
.
14.
Bucki
,
N.
, and
Mueller
,
M. W.
,
2019
, “
Design and Control of a Passively Morphing Quadcopter
,”
IEEE International Conference on Robotics and Automation (ICRA)
,
Montreal, Canada
,
May 20–24
, IEEE, pp.
9116
9122
.
15.
Bucki
,
N.
,
Tang
,
J.
, and
Mueller
,
M. W.
,
2022
, “
Design and Control of a Midair-Reconfigurable Quadcopter Using Unactuated Hinges
,”
IEEE Trans. Rob.
,
39
(
1
), pp.
539
557
.
16.
Bai
,
Y.
, and
Gururajan
,
S.
,
2019
, “
Evaluation of a Baseline Controller for Autonomous “Figure-8” Flights of a Morphing Geometry Quadcopter: Flight Performance
,”
Drones
,
3
(
3
), p.
70
.
17.
Desbiez
,
A.
,
Expert
,
F.
,
Boyron
,
M.
,
Diperi
,
J.
,
Viollet
,
S.
, and
Ruffier
,
F.
,
2017
, “
X-Morf: A Crash-Separable Quadrotor That Morfs Its X-Geometry in Flight
,”
Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS)
,
Linkoping, Sweden
,
Oct. 3–5
, IEEE, pp.
222
227
.
18.
Litvin
,
F.
, and
Yi
,
Z.
,
1986
, “
Robotic Bevel-Gear Differential Train
,”
Int. J. Rob. Res.
,
5
(
2
), pp.
75
81
.
19.
Ghosal
,
A.
,
2006
,
Robotics: Fundamental Concepts and Analysis
,
Oxford University Press
,
Oxford, UK
.
20.
Slotine
,
J.-J. E.
, and
Li
,
W.
,
1991
,
Applied Nonlinear Control
, Vol.
199
,
Prentice Hall Englewood Cliffs
,
NJ
.
21.
Spong
,
M. W.
, and
Vidyasagar
,
M.
,
2008
,
Robot Dynamics and Control
,
John Wiley & Sons
,
Hoboken, NJ
, pp.
217
218
.
22.
Theys
,
B.
,
Dimitriadis
,
G.
,
Hendrick
,
P.
, and
De Schutter
,
J.
,
2016
, “
Influence of Propeller Configuration on Propulsion System Efficiency of Multi-Rotor Unmanned Aerial Vehicles
,”
International Conference on Unmanned Aircraft Systems (ICUAS)
,
Arlington, VA
,
June 7–10
, IEEE, pp.
195
201
.
23.
Allison
,
S.
,
Bai
,
H.
, and
Jayaraman
,
B.
,
2020
, “
Wind Estimation Using Quadcopter Motion: A Machine Learning Approach
,”
Aerosp. Sci. Technol.
,
98
(
1
), p.
105699
.
24.
Jahnke
,
C. C.
,
1998
, “
On the Roll-Coupling Instabilities of High-Performance Aircraft
,”
Philos. Trans. R. Soc. London., Ser. A.
,
356
(
1745
), pp.
2223
2239
.
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