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Context-aware robot navigation based on sensor association rules

机译:基于传感器关联规则的上下文感知机器人导航

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Within the mobile robotics research community, a great many approaches have been proposed for solving the navigation problem. The key difference between these various navigation architectures is the manner in which they decompose the problem into smaller subunits. In this paper, a data mining methodology developed for the retrieving significant frequent patterns is extended to allow robots to learn and navigate on unknown terrain in natural way. The method has two phases: context identification phase and validation phase. Conjunction of those phases provides an easy and straightforward way for exploring new workings space for robots.
机译:在移动机器人研究界中,已经提出了一种解决导航问题的许多方法。这些各种导航架构之间的关键差异是它们将问题分解为较小亚基的方式。在本文中,延长了用于检索显着频繁模式的数据挖掘方法,以允许机器人以自然方式学习和导航未知的地形。该方法有两个阶段:上下文识别阶段和验证阶段。这些阶段的结合为探索机器人的新工作空间提供了一种简单而直接的方式。

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