A Comprehensive Review of Bio-Inspired Approaches to Coordination, Communication, and System Architecture in Underwater Swarm Robotics
- URL: http://arxiv.org/abs/2601.12244v1
- Date: Sun, 18 Jan 2026 03:42:28 GMT
- Title: A Comprehensive Review of Bio-Inspired Approaches to Coordination, Communication, and System Architecture in Underwater Swarm Robotics
- Abstract summary: Underwater swarm robotics offer a promising framework that extends the capabilities of individual autonomous platforms.<n>Inspired by natural systems, such as fish schools and insect colonies, bio-inspired swarm approaches enable distributed decision-making.<n>This review synthesises bio-inspired coordination mechanisms, communication strategies, and system design considerations.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The increasing complexity of marine operations has intensified the need for intelligent robotic systems to support ocean observation, exploration, and resource management. Underwater swarm robotics offers a promising framework that extends the capabilities of individual autonomous platforms through collective coordination. Inspired by natural systems, such as fish schools and insect colonies, bio-inspired swarm approaches enable distributed decision-making, adaptability, and resilience under challenging marine conditions. Yet research in this field remains fragmented, with limited integration across algorithmic, communication, and hardware design perspectives. This review synthesises bio-inspired coordination mechanisms, communication strategies, and system design considerations for underwater swarm robotics. It examines key marine-specific algorithms, including the Artificial Fish Swarm Algorithm, Whale Optimisation Algorithm, Coral Reef Optimisation, and Marine Predators Algorithm, highlighting their applications in formation control, task allocation, and environmental interaction. The review also analyses communication constraints unique to the underwater domain and emerging acoustic, optical, and hybrid solutions that support cooperative operation. Additionally, it examines hardware and system design advances that enhance system efficiency and scalability. A multi-dimensional classification framework evaluates existing approaches across communication dependency, environmental adaptability, energy efficiency, and swarm scalability. Through this integrated analysis, the review unifies bio-inspired coordination algorithms, communication modalities, and system design approaches. It also identifies converging trends, key challenges, and future research directions for real-world deployment of underwater swarm systems.
Related papers
- Topology-Driven Anti-Entanglement Control for Soft Robots [3.223232489699093]
This paper proposes a topology-driven Multi-Agent Reinforcement Learning (TD-MARL) framework to coordinate multi-robot systems to avoid entanglement.<n> Specifically, the critical network adopts centralized learning, so that each intelligent body can perceive the strategies of other intelligent bodies.<n>The integrated topological security layer uses topological invariants to accurately assess and mitigate the risk of entanglement to avoid the strategy from falling into local difficulties.
arXiv Detail & Related papers (2026-05-01T06:08:44Z) - Decentralized Heterogeneous Multi-Robot Collaborative Exploration for Indoor and Outdoor 3D Environments [11.81511178687002]
This paper proposes a decentralized collaborative framework for heterogeneous multi-robot systems.<n>The framework coordinates exploration tasks among heterogeneous robots, achieving superior exploration efficiency and communication savings.
arXiv Detail & Related papers (2026-04-26T13:16:13Z) - Underwater Embodied Intelligence for Autonomous Robots: A Constraint-Coupled Perspective on Planning, Control, and Deployment [9.865783767797874]
Review argues that planning and control must be understood within tightly coupled sensing, communication, coordination, and resource constraints in real ocean environments.<n>We show how environmental monitoring, inspection, exploration, and cooperative missions expose distinct stress profiles of cross-layer coupling.
arXiv Detail & Related papers (2026-03-08T00:45:06Z) - IMAGINE: Intelligent Multi-Agent Godot-based Indoor Networked Exploration [0.0]
This paper implements Multi-Agent Reinforcement Learning (MARL) to address challenges in a 2D indoor environment.<n>Policy training aims to achieve emergent collaborative behaviours and decision-making under uncertainty.
arXiv Detail & Related papers (2026-02-02T22:08:41Z) - Going Places: Place Recognition in Artificial and Natural Systems [17.238756001086344]
Review synthesizes findings from robotic systems, animal studies, and human research to explore how different systems encode and recall place.<n>We examine the computational and representational strategies employed across artificial systems, animals, and humans.<n>We propose a unifying set of concepts by which to consider and develop place recognition mechanisms.
arXiv Detail & Related papers (2025-11-18T10:49:14Z) - AI-Driven Marine Robotics: Emerging Trends in Underwater Perception and Ecosystem Monitoring [5.107513287801565]
Marine ecosystems face increasing pressure due to climate change, driving the need for scalable, AI-powered monitoring solutions.<n>This paper examines the rapid emergence of underwater AI as a major research frontier and analyzes the factors that have transformed marine perception into a catalyst for AI innovation.
arXiv Detail & Related papers (2025-09-02T01:51:31Z) - Decentralized Vision-Based Autonomous Aerial Wildlife Monitoring [55.159556673975544]
We propose a decentralized vision-based multi-quadrotor system for wildlife monitoring.<n>Our approach enables robust identification and tracking of large species in their natural habitat.
arXiv Detail & Related papers (2025-08-20T20:05:05Z) - A Review on Influx of Bio-Inspired Algorithms: Critique and Improvement Needs [0.8894489829970271]
Bio-inspired algorithms utilize natural processes such as evolution, swarm behavior, foraging, and plant growth to solve complex, nonlinear, high-dimensional optimization problems.<n>This survey categorizes these algorithms into eight groups: evolutionary, swarm intelligence, physics-inspired, ecosystem and plant-based, predator-prey, neural-inspired, human-inspired, and hybrid approaches.<n>We provide a critique on the novelty issues of many of these algorithms.
arXiv Detail & Related papers (2025-05-26T03:01:29Z) - Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey [58.50944604905037]
Edge-cloud collaborative computing (ECCC) has emerged as a pivotal paradigm for addressing the computational demands of modern intelligent applications.<n>Recent advancements in AI, particularly deep learning and large language models (LLMs), have dramatically enhanced the capabilities of these distributed systems.<n>This survey provides a structured tutorial on fundamental architectures, enabling technologies, and emerging applications.
arXiv Detail & Related papers (2025-05-03T13:55:38Z) - AI-Enhanced Automatic Design of Efficient Underwater Gliders [60.45821679800442]
Building an automated design framework is challenging due to the complexities of representing glider shapes and the high computational costs associated with modeling complex solid-fluid interactions.<n>We introduce an AI-enhanced automated computational framework designed to overcome these limitations by enabling the creation of underwater robots with non-trivial hull shapes.<n>Our approach involves an algorithm that co-optimizes both shape and control signals, utilizing a reduced-order geometry representation and a differentiable neural-network-based fluid surrogate model.
arXiv Detail & Related papers (2025-04-30T23:55:44Z) - Transforming the Hybrid Cloud for Emerging AI Workloads [82.21522417363666]
This white paper envisions transforming hybrid cloud systems to meet the growing complexity of AI workloads.<n>The proposed framework addresses critical challenges in energy efficiency, performance, and cost-effectiveness.<n>This joint initiative aims to establish hybrid clouds as secure, efficient, and sustainable platforms.
arXiv Detail & Related papers (2024-11-20T11:57:43Z) - Software Engineering for Collective Cyber-Physical Ecosystems [4.1185708189502215]
Today's distributed and pervasive computing addresses large-scale cyber-physical ecosystems.
Recent developments in fields such as self-organising systems and robotics swarm have opened up a complementary perspective: treating systems as "collectives"
This article explores the motivations, state of the art, and implications of this "collective computing paradigm" in software engineering.
arXiv Detail & Related papers (2024-06-07T09:28:22Z) - Simultaneous Navigation and Construction Benchmarking Environments [73.0706832393065]
We need intelligent robots for mobile construction, the process of navigating in an environment and modifying its structure according to a geometric design.
In this task, a major robot vision and learning challenge is how to exactly achieve the design without GPS.
We benchmark the performance of a handcrafted policy with basic localization and planning, and state-of-the-art deep reinforcement learning methods.
arXiv Detail & Related papers (2021-03-31T00:05:54Z) - A game-theoretic analysis of networked system control for common-pool
resource management using multi-agent reinforcement learning [54.55119659523629]
Multi-agent reinforcement learning has recently shown great promise as an approach to networked system control.
Common-pool resources include arable land, fresh water, wetlands, wildlife, fish stock, forests and the atmosphere.
arXiv Detail & Related papers (2020-10-15T14:12:26Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.