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Page 472 Phadke et al. Intell Robot 2023;3:453-78 https://dx.doi.org/10.20517/ir.2023.27

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their applications .

There are several directions that justify further exploration. A multi-objective optimization approach would
hold promise for balancing diverse objectives while enhancing resilience. Dynamic adaptation mechanisms,
powered by machine learning and AI, can facilitate real-time adjustments based on evolving conditions.
Additionally, fostering effective human-swarm interaction techniques and exploring innovative sensor
configurations can amplify the resilience of UAV swarms.

The significance of our findings resonates in the advancement of resilient UAV swarm applications across
[124]
various domains. From disaster response to agriculture , the potential impact on societal well-being is
substantial. This survey is designed to motivate readers to contemplate the intricate dynamics of UAV
swarm resilience, to critically assess their applicability within their fields, and to contribute to the ongoing
discourse in this area of research.

5. FUTURE RESEARCH DIRECTIONS
Few researchers have addressed the problem of swarm agent resilience and well-being as they perform their
assigned tasks. Depending on the resilience thresholds designed, the loss of several agents during mission
progress can affect the ability of the swarm to complete its mission. Even with tight constraints, some agents
can exhibit degraded performance and fail. As such, the swarm must have the capability for self-awareness
of the location and well-being of its agents. Previous studies have not addressed methodologies to track and
rescue their agents in the case that a loss occurs. SAR of swarm agents has been recognized as component
[15]
three by the authors of this study, where we found that there was almost no current research to reference
its implementation. One of the closest approaches to awareness policy by swarms to replace lost UAVs is
described in , which uses a replacement policy to replace lost UAVs. Recovery policies are almost absent
[125]
in current deployments where UAV swarm actively tries to recover lost agents. A different approach that
the authors of took was to design rescue depots and dynamic mission abort policies for swarm agent
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well-being. These are perfect examples of preliminary work on SS-SAR procedures.

The presence of heterogeneity in swarms can be categorized by a variety of factors, such as their hardware
buildup, operational space, and agent property. Operational space heterogeneity occurs when a swarm
comprises of agents working across a diverse target space, such as quadcopters and water surface vehicles
or ground-based rovers. Heterogeneity by nature is introduced when heterogeneity is induced by the
assigned operational characteristics in homogeneous hardware agents, such as a fast and slow agent or
exploratory and cautious agent combination swarms. Although challenging to address, heterogeneous
swarms have been observed to produce better performance, including co-evolution and the natural
emergence of agent capabilities [127,128] . This occurs due to complementary abilities brought about by
heterogeneous agents and extended thresholds on agent ability. Multiple demonstrations of operational
space combinations have been trialed, such as air-underwater vehicles , air-water surface , and air-
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[130]
[25]
ground vehicles . A selection of research exists that specifically targets heterogeneous agent issues in
swarms as discussed above in each category; however, prevalent issues with implementation along
with wide-ranging assumptions during experimental designs warrant further research.

6. CONCLUSION
This study conducts a general review of different application scenarios and the various novel resiliency
mechanisms that have been proposed to make swarms more efficient in accomplishing assigned goals. The
end goal of systemic resiliency research is the complete integration of such mechanisms in every facet of
system operation. This is an ambitious goal by itself, which requires ground-up development for all system