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Uncertainty analysis of a landmark initialization method for simultaneous localization and mapping

机译:同时定位和映射的地标初始化方法的不确定性分析

摘要

To operate successfully in any environment, mobile robots must be able to localize themselves accurately. In this paper, we describe a method to perform Simultaneous Localization and Mapping (SLAM) requiring only landmark bearing measurements taken along a linear trajectory. We solve the landmark initialization problem with only the assumption that the vision sensor of the robot can identify the landmarks and estimate their bearings. Contrary to existing approaches to landmark based navigation, we do not require any other sensors (like range sensors or wheel encoders) or the prior knowledge of relative distances between the landmarks. We provide an analysis of the uncertaintyudof the observations of the robot. In particular, we show how the uncertainty of the measurements is affected by a change of frames. That is, we determine what can an observer attached to a landmark frame deduce from the information transmitted by an observer attached to the robot frame. This SLAM system is ideally suited for the navigation of domestic robots such as autonomous lawn-mowers and vacuum cleaners.
机译:为了在任何环境中成功运行,移动机器人必须能够准确定位自己。在本文中,我们描述了一种执行同步定位和映射(SLAM)的方法,该方法仅需要沿线性轨迹进行地标方位测量。我们仅以机器人的视觉传感器可以识别地标并估计其方位的假设为前提来解决地标初始化问题。与基于地标的导航的现有方法相反,我们不需要任何其他传感器(例如距离传感器或车轮编码器),也不需要地标之间的相对距离的先验知识。我们提供了对机器人观测值的不确定性 ud的分析。特别是,我们显示了帧的变化如何影响测量的不确定性。也就是说,我们确定附在地标框架上的观察者可以从附在机器人框架上的观察者发送的信息中得出什么。该SLAM系统非常适合家用机器人的导航,例如自动割草机和吸尘器。

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