Applications of Multi-Agent Systems in Unmanned Surface Vessels

Maleš, Lada; Sumić, Dean; Rosić, Marko

doi:10.3390/electronics11193182

Cited by 7 publications

(4 citation statements)

References 38 publications

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“…The development of agent-based autonomous ship subsystems is a current trend in the further development of autonomous vessels (Males et al, 2022). An agent is an entity that is autonomous and possesses the properties of reactivity, proactivity, and sociability.…”

Section: Figure 2 Breakdown Of Ship Subsystemsmentioning

confidence: 99%

“…Figure 3. Agent structure (Males et al, 2022) Suitable interoperability infrastructure needs to be developed to ensure effective collaboration. The implementation of ontologies into the information infrastructure of autonomous ships facilitates the use of intelligent agents, which is yet another motivation for further research in this field.…”

Section: Figure 2 Breakdown Of Ship Subsystemsmentioning

confidence: 99%

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Ontology-Based Information Infrastructure for Autonomous Ships

Sumić,

Maleš,

Marušić

et al. 2024

Trans. Marit. Sci.

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The maritime industry is witnessing a revolutionary transformation with the development of autonomous ships. Unmanned vessels employ advanced technologies such as artificial intelligence, especially machine learning, and intelligent agents for autonomous navigation. The successful integration of autonomous ships into existing maritime ecosystems requires a robust infrastructure capable of addressing various challenges, including interoperability of different ship systems. To ensure interoperability, it is crucial to establish a suitable information infrastructure. The implementation of ontologies within the information infrastructure of autonomous ships facilitates the use of intelligent agents. This paper discusses the concept of ontological information infrastructure tailored for autonomous ships and gives an example of an ontology designed specifically for autonomous vessel firefighting systems.

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Section: Figure 2 Breakdown Of Ship Subsystemsmentioning

confidence: 99%

Section: Figure 2 Breakdown Of Ship Subsystemsmentioning

confidence: 99%

Ontology-Based Information Infrastructure for Autonomous Ships

Sumić,

Maleš,

Marušić

et al. 2024

Trans. Marit. Sci.

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“…Regrettably, these strategies are marred by suboptimal processing efficiency. Furthermore, an alternative avenue involves employing reinforcement learning [29][30][31], swarm intelligence algorithms [32][33][34], and game theory as planning mechanisms. However, these approaches grapple with challenges such as intensive computation and marginal impact on the overall solution effectiveness.…”

Section: Related Workmentioning

confidence: 99%

Optimizing Port Multi-AGV Trajectory Planning through Priority Coordination: Enhancing Efficiency and Safety

Chen,

Shi,

Chen

et al. 2023

Axioms

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Efficient logistics and transport at the port heavily relies on efficient AGV scheduling and planning for container transshipment. This paper presents a comprehensive approach to address the challenges in AGV path planning and coordination within the domain of intelligent transportation systems. We propose an enhanced graph search method for constructing the global path of a single AGV that mitigates the issues associated with paths closely aligned with obstacle corner points. Moreover, a centralized global planning module is developed to facilitate planning and scheduling. Each individual AGV establishes real-time communication with the upper layers to accurately determine its position at complex intersections. By computing its priority sequence within a coordination circle, the AGV effectively treats the high-priority trajectories of other vehicles as dynamic obstacles for its local trajectory planning. The feasibility of trajectory information is ensured by solving the online real-time Optimal Control Problem (OCP). In the trajectory planning process for a single AGV, we incorporate a linear programming-based obstacle avoidance strategy. This strategy transforms the obstacle avoidance optimization problem into trajectory planning constraints using Karush-Kuhn-Tucker (KKT) conditions. Consequently, seamless and secure AGV movement within the port environment is guaranteed. The global planning module encompasses a global regulatory mechanism that provides each AGV with an initial feasible path. This approach not only facilitates complexity decomposition for large-scale problems, but also maintains path feasibility through continuous real-time communication with the upper layers during AGV travel. A key advantage of our progressive solution lies in its flexibility and scalability. This approach readily accommodates extensions based on the original problem and allows adjustments in the overall problem size in response to varying port cargo throughput, all without requiring a complete system overhaul.

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“…With the development of network information technology and the era of artificial intelligence, multi-agent systems (MASs) have received extensive attention in view of their applications in the machining industry [1], synchronous generators [2], microservice-based cloud applications [3], USVs [4], and other fields. It is worth noting that consensus is one of the most fundamental and important problems in MASs, and there have been many studies about it [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Distributed Optimization for Resource Allocation Problem with Dynamic Event-Triggered Strategy

Guo

Chen

Ming

et al. 2023

Entropy

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This study aims to unravel the resource allocation problem (RAP) by using a consensus-based distributed optimization algorithm under dynamic event-triggered (DET) strategies. Firstly, based on the multi-agent consensus approach, a novel one-to-all DET strategy is presented to solve the RAP. Secondly, the proposed one-to-all DET strategy is extended to a one-to-one DET strategy, where each agent transmits its state asynchronously to its neighbors. Furthermore, it is proven that the proposed two types of DET strategies do not have Zeno behavior. Finally, numerical simulations are provided to validate and illustrate the effectiveness of the theoretical results.

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Applications of Multi-Agent Systems in Unmanned Surface Vessels

Cited by 7 publications

References 38 publications

Ontology-Based Information Infrastructure for Autonomous Ships

Ontology-Based Information Infrastructure for Autonomous Ships

Optimizing Port Multi-AGV Trajectory Planning through Priority Coordination: Enhancing Efficiency and Safety

Distributed Optimization for Resource Allocation Problem with Dynamic Event-Triggered Strategy

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