Unmanned Underwater Vehicle (UUV) formation system has an important role in the utilization of marine resource. In order to provide an efficient method to research modeling and simulation of UUV formation in the marine environment, the novel approach based on Multi-Agent Interaction Chain was proposed for the UUV formation system. Firstly, Multi-Agent Interaction Chain was analyzed, which mainly considered task and role of UUV in the formation, and the overall modeling process of UUV formation system based on Multi-Agent Interaction Chain was established. Then, the static structure of Multi-Agent Interaction Chain was researched focusing on Hybrid UUV-Agent model structure from the UUV-Agent State-Set and UUV-Agent Rule-Base which were the two aspects to strengthen reliability of interaction chain; the dynamic mechanism of Multi-Agent Interaction Chain was designed, which was focused on collaboration model and communication model through the Adaptive Dynamic Contract Net Protocol and KQML/XML/RTI. Finally, three experiments were established to verify the validity and effectiveness of proposed modeling approach for UUV formation system. Simulation results show the proposed model has good performance, which has important theoretical innovation and application prospects.
One of most primitive problems by unmanned underwater vehicle intelligent swarm (UIS) is coordination control, which has a great significance for realization of target hunting with great performance of efficiency and robustness. Existing studies concentrate on behavior-based centralized or distributed control approaches with the prior knowledge and mostly do not elaborately consider behavior conflicts and constraint differences. Therefore, a novel behavior-driven coordination control framework including topology architecture and swarm control which is inspired by immune mechanism, is investigated for target hunting of heterogeneous UIS under unknown and uncertain environment in this paper. For topology architecture, a hybrid non-central distributed topology is developed as a novel immune-inspired architecture to regulate agents with self-organizational and fault-tolerance features. For swarm control, a dual-layer switching control scheme composed by global control and local control, is proposed to drive behaviors via behavioral-intensity, the trigger of switching is when the target is detected. The global control approach is employed to search target, in which two constraints of energy consumption and healthy-state are considered to achieve good operational reliability. While the local control approach is developed to form the dynamic alliance of tracking and capturing, in which behavioral-intensity control strategy for behavior aggregation and decision-making control strategy for behavior selection are respectively designed to avoid behavior conflicts. Simulation results demonstrate that proposed framework can accomplish hunting under various situations such as hunter agent is random or fixed distribution, and the number of targets asynchronously appears. It is confirmed that our framework is capable of achieving the target hunting under unknown and uncertain environment with greater efficiency and robustness. INDEX TERMS Target hunting, behavior-driven, coordination control, hybrid non-central topology, dual-layer switching control.
We introduce an automatic optimization approach for the simulation of large-scale coastal water. To solve the singular problem of water waves obtained with the traditional model, a hybrid deep-shallow-water model is estimated by using an automatic coupling algorithm. It can handle arbitrary water depth and different underwater terrain. As a certain feature of coastal terrain, coastline is detected with the collision detection technology. Then, unnecessary water grid cells are simplified by the automatic simplification algorithm according to the depth. Finally, the model is calculated on Central Processing Unit (CPU) and the simulation is implemented on Graphics Processing Unit (GPU). We show the effectiveness of our method with various results which achieve real-time rendering on consumer-level computer.
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