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Real-time motion planning in autonomous vehicles: a hybrid approach

机译:自动车辆的实时运动规划:一种混合方法

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In this paper a multi-agent architecture of an Autonomous Robot Navigator for a vehicle that operates in dynamic real-world environments is presented. The vehicle is capable of executing different navigation msissions while smoothly avoiding static obstacles in its path as well as moving objects. SThe navigator architecture is part of a general multi-agent cognitive framework, which is organised into three non-hierarchical components characterised by the type of knowledge they deal with: a symbolic component, handling a declarative explicit propositional formalism, a diagrammatic component, dealing with analogical, iconic representations, and a reactive behaviour based component. The navigator is distributed in all three components combining motion planning on a topological graph with reactive motion planning techniques. It is on these aspects that the paper focuses. Experimental results with our mobile robot will also be provided.
机译:本文提出了一种在动态现实世界环境中运行的车辆的自主机器人导航器的多代理体系结构。该车辆能够执行不同的导航光照,同时平滑地避免其路径中的静态障碍以及移动物体。 STHE Navigator架构是一般多代理认知框架的一部分,该框架被组织成三个非分层组件,其特征在于它们处理的知识类型:符号组件,处理声明的明确命题形式主义,一个图解组件,处理类比,标志性表示和基于反应性的组件。导航器分布在所有三个组件中,将运动规划的所有三个组件分布在具有无功运动规划技术的拓扑图中。这是纸张侧重于这些方面。还将提供我们的移动机器人的实验结果。

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