Citation: Jin, Z.; Nie, L.; Li, D.; Tu, Z.;
Xiang, J. An Autonomous Control
Framework of Unmanned Helicopter
Operations for Low-Altitude Flight
in Mountainous Terrains. Drones
2022, 6, 150. https://doi.org/
10.3390/drones6060150
Academic Editors: Andrzej
Łukaszewicz, Wojciech Giernacki,
Zbigniew Kulesza, Jaroslaw Pytka
and Andriy Holovatyy
Received: 1 June 2022
Accepted: 14 June 2022
Published: 17 June 2022
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Article
An Autonomous Control Framework of Unmanned Helicopter
Operations for Low-Altitude Flight in Mountainous Terrains
Zibo Jin
1
, Lu Nie
2
, Daochun Li
1
, Zhan Tu
1,3,
* and Jinwu Xiang
1
1
School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China;
jinzibo@buaa.edu.cn (Z.J.); lidc@buaa.edu.cn (D.L.); xiangjw@buaa.edu.cn (J.X.)
2
Beijing Institute of Space Long March Vehicle, Beijing 100076, China; nielu@buaa.edu.cn
3
Institute of Unmanned System, Beihang University, Beijing 100191, China
* Correspondence: zhantu@buaa.edu.cn; Tel.: +86-(010)-82338079
Abstract:
Low-altitude flight in mountainous terrains is a difficult flight task applied in both military
and civilian fields. The helicopter has to maintain low altitude to realize search and rescue, reconnais-
sance, penetration, and strike operations. It contains complex environment perception, multilevel
decision making, and multi-objective flight control; thus, flight is currently mainly conducted by
human pilots. In this work, a control framework is implemented to realize autonomous flight for
unmanned helicopter operations in an unknown mountainous environment. The identification of
targets and threats is introduced using a deep neural network. A 3D vector field histogram method
is adopted for local terrain avoidance based on airborne Lidar sensors. In particular, we propose
an intuitive direct-viewing method to judge and change the visibilities of the helicopter. On this
basis, a finite state machine is built for decision making of the autonomous flight. A highly realistic
simulation environment is established to verify the proposed control framework. The simulation
results demonstrate that the helicopter can autonomously complete flight missions including a fast
approach, threat avoidance, cover concealment, and circuitous flight operations similar to human
pilots. The proposed control framework provides an effective solution for complex flight tasks and
expands the flight control technologies for high-level unmanned helicopter operations.
Keywords:
autonomous flight control; unmanned helicopter operation; terrain avoidance; visual
servo control; threat avoidance
1. Introduction
Unmanned aerial vehicles (UAVs) have received substantial interest from the research
community and the general public alike in recent years [
1
,
2
], especially small UAVs and
multi-rotors, whose low cost and convenient use provide ideal testbeds and development
impetus for innovative technologies of control approaches [
3
,
4
], advanced intelligent
perception [
5
], and complete autonomy [
6
–
9
]. Small and medium UAVs can hardly meet the
demands of high payloads and long flight distances. Therefore, more and more large-scale
UAVs are being developed to provide long-endurance flights and perform various missions
like manned aircraft. There are also related research projects developing independent
autonomous equipment [
10
,
11
] or executing modifications [
12
] to convert manned aircraft
to UAVs. There is a great need to investigate autonomy flight technologies for application
scenarios of large-scale UAVs, manned aircraft, and helicopters for unmanned operations.
Helicopters demonstrate unique characteristics of maneuverability and low-speed
performance, significantly extending their application in both military and civil fields [
13
].
With the development of advanced sensing devices and technologies, various sensor sys-
tems including cameras, radar, laser/light detection and ranging (Lidar), electro-optical
(EO) system, acoustic system, and infrared (IR) sensors are deployed on helicopters to
Drones 2022, 6, 150. https://doi.org/10.3390/drones6060150 https://www.mdpi.com/journal/drones
