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A Model for Bio-Inspired Underwater Swarm Robotic Exploration

机译:生物启发水下群机器人勘探模型

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Swarm intelligence has interested researchers in various areas of research for several decades because of its stability, resilience and simplicity. Several researchers have used swarm intelligence behaviours to design systems which can accomplish single tasks. In this paper, we will make a step forward by designing a swarm intelligent system that draws from two different natural swarms, bees and slime mould, to form an integrated underwater swarm robotic exploration system. An agent based simulation of such a system is presented in this paper along with some basic performance evaluation measures of the presented system. The main question the authors are attempting to answer through this model is how feasible the such an exploration system would be with regards to time, the number of robots allocated by the decentralized system for exploring interesting locations and the resilience of such a system to failures in robots. The first simulation results obtained from this model shows how decentralized control inspired by swarm intelligence can be used to design systems for real world applications.
机译:由于其稳定性,恢复力和简单,群体智能对各种研究领域感兴趣的研究人员感兴趣。几位研究人员使用了群体智能行为来设计可以完成单一任务的系统。在本文中,我们将通过设计一个从两种不同的自然群,蜜蜂和粘液模具绘制的繁华智能系统来迈出一步,以形成一条集成的水下群机器人勘探系统。本文提出了一种基于代理的这种系统的模拟,以及所呈现的系统的一些基本性能评估措施。作者通过这一模型试图回答的主要问题是这种探索系统在时间方面是多么可行的,分散系统分配的机器人数量探索有趣的位置以及这种系统的恢复力来失败机器人。从该模型中获得的第一个仿真结果显示了由群智能启发的分散控制如何用于设计现实世界应用的系统。

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