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Semi-Autonomous Navigation for Virtual Tactical Simulations in the Military Domain

机译:军事域中虚拟战术模拟的半自动导航

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Integrated constructive and virtual simulations are becoming popular for tactical training in the military domain. An important aspect concerning the integration of these simulation models in the construction of virtual tactical simulations is the modelling and implementation of different kinds of semi-autonomous agents. A fundamental feature of these agents is the capability of intelligently and realistically modelling task-oriented navigation activities in large virtual terrain simulation environments, while following underlying military doctrine and tactics. This paper reviews important navigation issues that emerge in such simulation systems and prominent Artificial Intelligence (AI) techniques that have been explored to solve them. From this analysis, a hybrid, semi-autonomous navigation framework is proposed aiming to fulfil the needs of virtual tactical training simulations, more specifically, in the military domain. As implemented in a system for the virtual tactical simulation of artillery battery tasks, the framework shows how to overcome the challenges of implementing realistic global and local navigation behaviours for military units and, at the same time, it shows that the semi-autonomous behaviours implemented are of primary importance to allow interaction with users for learning purposes in the simulation exercises.
机译:集成的建设性和虚拟模拟正在成为军事领域的战术训练的流行。关于虚拟战术模拟建设中这些仿真模型的集成的一个重要方面是不同种类的半自动代理的建模与实现。这些代理的基本特征是在大型虚拟地形模拟环境中智能地和实际建模的任务导航活动的能力,同时涉及潜在的军事学说和战术。本文审查了在这种仿真系统中出现的重要导航问题,并探讨了解决这些系统的突出人工智能(AI)技术。从这个分析中,提出了一种混合动力车,半自动导航框架,旨在满足虚拟战术训练模拟的需求,更具体地,在军事领域。如在用于虚拟战术模拟的系统中实施的火炮电池任务,该框架展示了如何克服为军事单位实施现实全球和本地导航行为的挑战,同时它表明实施了半自治行为允许与用户互动以进行模拟练习中的学习目的的互动。

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