# Swarm Robotics: A Perspective on the Latest Reviewed Concepts and Applications
## 6 Applications Using Swarm Robotics
### Marine Environmental Control  
As presented in the introductory section, swarms are compositions of autonomous robots. Unmanned Underwater Vehicles (UUVs) and Unmanned Surface Vehicles (USVs) allow the usage of swarms in several tasks. For instance, swarm robotics in UUVs and USVs improve automated environmental monitoring in marine environments [137], oil pollution control [138], and exploration [139]. The applicability of swarm robotics in these environments led to the development of specific simulation tools for these environments, such as microUSV [60]. [PERSON] and [PERSON] [60] introduce an open-source Unmanned Surface Vehicle (USV) projected to act in laboratory ambiances. The first design objective was to minimize the robot's dimension and cost while demonstrating a steady and maneuverable platform with autonomy. To achieve this, the robot is constructed using 3D printed, electronic components and uses a general camera system to simulate sensor data to minimize the number of onboard sensors needed. Their paper reports the context, project, and montage process for a microUSV and shows the platform's base-level functionality in the mold of a controller implementation for either single and multi-agent configuration. In their paper, [PERSON] and [PERSON] [138] uses a swarm intelligence algorithm, Modified GlowwormSwarm optimization (MGSO) Algorithm, jointly as swarm robots to find out origins of oil pours. Their algorithm uses a variant step size on a static method profile to accelerate the convergence fee. The result shows superior performance if the quantity of iteration and quantity of s-bots get reduced. The comparing analysis is produced by using some benchmark function and estimations measurements based on PCR (Peak Captured Rate). The most significant quantity of origins of oils' pours is discovered. [PERSON] et al. [137] presents a study of an underwater acoustic sensor network compounded of a heterogeneous robotic swarm used for a long-period scanning underwater ambiances. This swarm contains many underwater robots performing as sensor nodes with restricted motion capacities, and some surface robots assist them in realizing subaqueous overseeing scenarios. Principals interaction between two kinds of robots embraces underwater sensor deployment and relocation, energy and data exchange, and acoustic localization assistance. The hardware capacities of each agent have described inexactness. Agents communication is divided into two tiers: surface and subaqueous communication. Surface communication employs wireless communication using Wi-Fi routers with decentralized routing. Subaqueous communication mostly works with acoustic communication that poses a defiance task whenever used in a wide swarm because of the extreme possibility of interference and data loss. The acoustic communication protocol used to avoid these questions is described in detail. Lastly, additional complicated functionalities of SR are introduced, including sundry results from life-real tests. In the study of [PERSON] et al. [139], they create an autonomous multi-robot approach to investigate unfamiliar subaqueous ambiances by gathering data about water features and the existence of barriers. Unfamiliar subaqueous spaces are adverse ambiances whose exploration is frequently complicated. The usage of human diapers or equipped vehicles for these scenarios imply significant danger and massive overheads. The systems used for the same tasks generally entrust remotely operated vehicles (ROVs) commanded by a human operator. The troubles related to this technique embrace the substantial costs of hiring a high prepared operator, the necessary presence of a vehicle in closeness to the ROV, and the delay in communication frequently experienced between the operator and the ROV. Their study propounds the usage of autonomous agents that would allow costs to be quite decreased. Furthermore, a distributed swarm method would enable the ambiance to be investigated faster and effectively instead of using a unique robot.