Performance Evaluation of Incremental Eigenspace Models for Mobile Robot Localization
Performance Evaluation of Incremental Eigenspace Models for Mobile Robot Localization
复制标题
移动机器人定位增量特征空间模型的性能评估
DOI：
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发表时间：
2003
期刊：
影响因子：
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通讯作者：
T. Bastos
中科院分区：
文献类型：
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作者：
R. Freitas;J. Santos;M. Sarcinelli;T. Bastos
我们解决的问题，机器人定位的基础上的特征空间表示的工作空间的意见，通常被称为外观为基础的方法的集合。我们研究了几种方法来建立这样的特征空间在一个增量的方式（子空间跟踪），从而允许同时定位和映射的移动的车辆。我们看到，确定新信息（图像）是否应该包含在特征空间模型中的不同方法如何导致更大的误差值和模型大小（复杂性）。性能评估允许我们知道在特定应用中使用哪些标准和参数来满足受计算约束的误差规格。
We address the problem of robot localization based on eigenspace representations of a collection of views of the workspace, often referred to as appearance based methods. We study several approaches to build such eigenspaces in an incremental fashion (subspace tracking), thereby allowing the simultaneous localization and mapping of a mobile vehicle. We see how different ways of determining whether or not new information (images) should be included in the eigenspace model lead to dier ent error values and model size (complexity). The performance evaluation allows us to know which criterion and parameters to use in a specic application to meet error specic ations subject to computational constraints.