Current Algorithms, Communication Methods and Designs for Underwater Swarm Robotics: A Review

Connor, J. W.; Champion, Benjamin; Joordens, Matthew

doi:10.1109/jsen.2020.3013265

Cited by 42 publications

(16 citation statements)

References 164 publications

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“…Then, the receiver calculates the prediction of the hybrid channel state Xt using the relation in (23) and collects the observations. The value of the observation function is defined in (21). While the optical communication is OFF, the measurement function Z t is obtained by the blind estimation which combines the theoretical value of optical SNR O and the acoustic measurement SNR A using the relation in (17).…”

Section: The Description Of the Proposed Switching Algorithmmentioning

confidence: 99%

“…Since a fleet of AUVs are desirable mobile vehicles to perform flexible underwater tasks under operational scenarios, such as environment monitoring, security surveillance, and underwater asset investigation [1,20], the study focused on leveraging a swarm of AUVs to form underwater mobile networks has been developing rapidly in the recent years [3,21]. By networking a swarm of AUVs equipped with both optical and acoustic communication systems, such a hybrid network enables high-bandwidth and low-latency underwater video transmission and real-time underwater operation and control [9,22].…”

Section: Introductionmentioning

confidence: 99%

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Reinforcement Learning-Based Adaptive Switching Scheme for Hybrid Optical-Acoustic AUV Mobile Network

Luo

Wang

et al. 2022

Wireless Communications and Mobile Computing

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In an autonomous underwater vehicles– (AUVs–) based optical-acoustic hybrid network, it is critical to achieve ultra high-speed reliable communications, in order to reap the benefits of the complementary systems and perform high-bandwidth and low-latency operations. However, as the mobile AUVs operate in harsh oceanic environments, it is essential to design an effective switching algorithm to execute flexible hybrid acoustic-optical communications and increase the network throughput. In this paper, we propose a Q-learning-based adaptive switching scheme to maximize the network throughput by capturing the dynamics of the varying channels as well as the mobility of AUVs. In order to address the challenge associated with partial observations of the optical channel and improve the switching efficiency in extreme conditions, a blind optical channel estimation method is designed and implemented with the Extended Kalman Filter (EKF), in which the relationship between the underwater acoustic and optical channels is utilized to improve the channel prediction accuracy. Based on this environmental status, a reinforcement learning approach is leveraged to build a near-optimal switching strategy for the hybrid network. We conduct numerical simulations to verify the performance of the scheme, and the simulation results demonstrate that the proposed switching scheme is effective and robust.

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Section: The Description Of the Proposed Switching Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reinforcement Learning-Based Adaptive Switching Scheme for Hybrid Optical-Acoustic AUV Mobile Network

Luo

Wang

et al. 2022

Wireless Communications and Mobile Computing

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“…AUV swarms are a recent but emerging development [5]. Like their counterparts in terrestrial-based and air-based applications, called unmanned ground vehicles and unmanned aerial vehicles, AUV swarms are motivated by schools of fish, flocks of birds, and swarms of social insects.…”

Section: A Background On Auvs and Auv Swarmsmentioning

confidence: 99%

Underwater Optical Wireless Communications in Swarm Robotics: A Tutorial

Hoeher

Sticklus

Harlakin

2021

IEEE Commun. Surv. Tutorials

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Underwater swarm robotics is an emerging topic. Compared to individual autonomous vehicles, high-capacity communication links are required between the mobile agents. In this tutorial, suitable communication technologies are studied, with emphasis on LED-based underwater optical wireless communications. A comprehensive overview about challenges, advances, and practical aspects of underwater swarm robotics employing optical wireless communications is provided. The tutorial includes the following topics: (1) Channel modeling fundamentals; (2) Physical layer transmission techniques for underwater optical wireless communications; (3) Data link layer aspects and hybrid transmission schemes; (4) Ambient light and interference suppression; and (5) Realization aspects. Finally, suggestions regarding future work are given. The tutorial is intended for readers with a background or interest in electrical and information engineering.Index Terms-Autonomous underwater vehicles, channel models, free-space optical communication, light emitting diodes, physical layer, swarm robotics, underwater communication, unmanned underwater vehicles, vehicular ad hoc networks, visible light communication.

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“…The most promising approach to improve the performance of visual underwater surveys is the implementation of a multi-robot approach, specifically a swarm approach [10,11]. The first obvious advantage lies in the possibility to parallelize the job among multiple agents: this not only allows for lower operating times and costs, but enables wide area studies when the time frame for the data acquisition impacts the measurements (for example: when studying fauna active only at a certain time of the day, or chemical proprieties with a 3d pattern or vertical stratification).…”

Section: Introductionmentioning

confidence: 99%

Heterogeneous Underwater Swarm of Robotic Fish

Iacoponi,

Hanbaly,

Infanti

et al. 2023

IOP Conf. Ser.: Mater. Sci. Eng.

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Underwater robotics is prevalent today in the field of undersea surveys. The current single-agent approach struggles to cover surveys of large areas, especially when visual analyses are required. Applications of underwater multi-robots fleets need to manage the coordination of the agents, which in turn stresses the already limited capabilities of underwater localization and communication. We propose a concept for a multilayered control architecture, which leverages visual recognition and swarm behavior to negotiate the coordination requirements of the single agent while retaining a significant level of control over the fleet of vehicles as a whole. This is obtained by including multiple control layers, paired with a heterogeneous composition of vehicles.

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Current Algorithms, Communication Methods and Designs for Underwater Swarm Robotics: A Review

Cited by 42 publications

References 164 publications

Reinforcement Learning-Based Adaptive Switching Scheme for Hybrid Optical-Acoustic AUV Mobile Network

Reinforcement Learning-Based Adaptive Switching Scheme for Hybrid Optical-Acoustic AUV Mobile Network

Underwater Optical Wireless Communications in Swarm Robotics: A Tutorial

Heterogeneous Underwater Swarm of Robotic Fish

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