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Page 454 Phadke et al. Intell Robot 2023;3:453-78 https://dx.doi.org/10.20517/ir.2023.27

collective behaviors to achieve complex tasks with minimal human oversight, epitomizing the confluence of
advancements in electronics, communication technology, and algorithmic design.

The miniaturization of electronics has been instrumental in the evolution of UAV swarms. With the advent
of compact microcontrollers, powerful computation can be integrated into relatively small drone chassis.
Concurrently, the incorporation of Micro-Electro-Mechanical Systems (MEMS) sensors , including
[1]
accelerometers, gyroscopes, and magnetometers, ensures robust Attitude and Heading Reference
systems (AHRS) for individual UAVs. Communication remains central to the efficacy of UAV
swarms, necessitating low latency and high reliability. Modern swarms predominantly employ
protocols such as Zigbee, LoRa , or customized 2.4 GHz RF modules, with a distinct bias toward mesh
[2,3]
network topologies, ensuring redundancy and robustness in intra-swarm communications. These
communication frameworks, when coupled with decentralized control algorithms, such as consensus
algorithms, distributed task allocation, and flocking behaviors, enable UAVs to exhibit collective
intelligence.

At the core of each UAV in the swarm is a combination of onboard processors, sensor suites comprising
Inertial Measurement Units (IMUs) , Global Navigation Satellite System (GNSS) receivers and
[4]
transponders, and vision systems using cameras or Light Detection and Ranging (LiDAR) for
[5]
Simultaneous Localization And Mapping (SLAM) applications and communication modules that
[6]
sustain the necessary connectivity within the swarm and potentially with human operators.

With advancements in battery technology, particularly the ubiquity of high-energy-density Li-Po and Li-ion
batteries, along with the efficiency of brushless DC motors, UAVs are now more enduring and agile than
ever. Collectively, these innovations underpin the burgeoning potential of UAV swarms, positioning them
as a transformative force in a diverse array of sectors, ranging from agriculture and defense to urban
planning and entertainment.

Resiliency is a broad term that encompasses the ability of a system to continue working at acceptable
performance levels despite disruptions. While conceptually, it can be defined as system rebound, inherent
[7]
robustness, graceful extensibility, and unconstrained adaptability , these are a literary representation of
ideal system characteristics to unwanted stimuli, external or internal. The study of resilience as applied to
Unmanned Aerial Systems (UAS) has been widespread in the literature, and the problem is approached
from various directions. Sometimes, addressing key components of the systemic makeup, such as trying to
solve networking or area coverage issues, or sometimes, addressing the system as a whole . This study
[8,9]
performs a categorization of application-specific UAV swarms and their resilience mechanisms and
condenses it into a structural representation. The review structure is summarized in Figure 1.

To curate the literature required for the review and updated insight into current trends, articles on UAV
swarms published in the last five years (2019 to June 2023) were examined. The search was conducted using
popular scientific databases, including Scopus, Science Direct, Web of Science, and Google Scholar. Out of
the total 572 articles that were examined, 67 were survey articles that were removed. Figure 2 outlines the
basic outline for the literature collection . Articles that explicitly do not make use of UAV swarms for an
[10]
application were removed. These include dataset descriptors and machine learning and image processing
[11]
methodologies using UAV imagery and sensor data.

The remaining articles were then classified into one of the three categories that were established. Figure 3
visualizes the literature divided into these three categories.