Citation: Belge, E.; Altan, A.;
Hacıo˘glu, R. Metaheuristic
Optimization-Based Path Planning
and Tracking of Quadcopter for
Payload Hold-Release Mission.
Electronics 2022, 11, 1208. https://
doi.org/10.3390/electronics11081208
Academic Editors: Luis
Hernández-Callejo, Sergio
Nesmachnow and Sara Gallardo
Saavedra
Received: 12 March 2022
Accepted: 8 April 2022
Published: 11 April 2022
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Article
Metaheuristic Optimization-Based Path Planning and Tracking
of Quadcopter for Payload Hold-Release Mission
Egemen Belge , Aytaç Altan and Rıfat Hacıo˘glu *
Department of Electrical and Electronics Engineering, Zonguldak Bülent Ecevit University,
67100 Zonguldak, Turkey; egemenbelge@beun.edu.tr (E.B.); aytacaltan@beun.edu.tr (A.A.)
* Correspondence: hacirif@beun.edu.tr
Abstract:
Under harsh geographical conditions where manned flight is not possible, the ability of
the unmanned aerial vehicle (UAV) to successfully carry out the payload hold–release mission by
avoiding obstacles depends on the optimal path planning and tracking performance of the UAV.
The ability of the UAV to plan and track the path with minimum energy and time consumption is
possible by using the flight parameters. This study performs the optimum path planning and tracking
using Harris hawk optimization (HHO)–grey wolf optimization (GWO), a hybrid metaheuristic
optimization algorithm, to enable the UAV to actualize the payload hold–release mission avoiding
obstacles. In the study, the hybrid HHO–GWO algorithm, which stands out with its avoidance of
local minima and speed convergence, is used to successfully obtain the feasible and effective path. In
addition, the effect of the mass change uncertainty of the UAV on optimal path planning and tracking
performance is determined. The effectiveness of the proposed approach is tested by comparing it
with the metaheuristic swarm optimization algorithms such as particle swarm optimization (PSO)
and GWO. The experimental results obtained indicate that the proposed algorithm generates a fast
and safe optimal path without becoming stuck with local minima, and the quadcopter tracks the
generated path with minimum energy and time consumption.
Keywords:
path planning and tracking; metaheuristic optimization; quadcopter; payload hold–
release system; obstacle avoidance
1. Introduction
Path planning and tracking are the main tasks studied for unmanned vehicles, es-
pecially unmanned aerial vehicles (UAVs), unmanned ground vehicles, and unmanned
underwater vehicles [
1
–
4
]. UAVs, which have been used extensively in defense industry
and academic studies in recent years, perform tasks such as surveillance, target tracking,
search and rescue, and payload transportation [
4
–
7
]. The obstacles and their positions in
the region where UAVs will operate play an important role in the effective operation of
UAVs [
8
]. Establishing a safe path by determining the risky areas in military operation
and natural disaster areas, following the path that has been generated, and releasing the
payloads to the predefined regions are critical for the successful performance of the mis-
sion [
9
]. In this study, a new path planning and tracking algorithm based on metaheuristic
optimization is developed for the payload hold–release task by avoiding the obstacles at
the target points defined around the planned path.
A path planning and tracking is required for the UAV to safely reach the target location
from the starting location depending on certain restriction conditions such as minimum
flight distance and time [
10
]. UAVs may be exposed to inconvenient land and weather
conditions while performing critical tasks. UAVs try to overcome this problem with their
maneuverability and altitude capabilities [
1
]. This situation causes the UAV to consume
more energy [
11
]. In the presence of obstacles and constraints, optimal path planning
is required for the UAV to safely follow the specified path with minimum energy and
time consumption [
12
,
13
]. The UAV path planning problem is a complex optimization
Electronics 2022, 11, 1208. https://doi.org/10.3390/electronics11081208 https://www.mdpi.com/journal/electronics
