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An evidential approach to probabilistic map-building

机译:概率地图构建的证据方法

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Examines the problem of constructing and maintaining a map of of an autonomous vehicle's environment for the purpose of navigation, using evidential reasoning. The inherent uncertainty in the origin of measurements of sensors demands a probabilistic approach to processing, or fusing, the new sensory information to build an accurate map. In this paper, the map is based on a two-dimensional occupancy grid. The sensor readings are 'fused' into the map using the Dempster-Shafer inference rule. This evidential approach with its multi-valued hypotheses allows quantitative analysis of the quality of the data. The map building system is experimentally evaluated using sonar data from real environments.
机译:使用证据推理,检查为导航目的构建和维护自动驾驶汽车环境地图的问题。传感器测量源的固有不确定性要求采用概率方法来处理或融合新的传感信息以构建准确的地图。在本文中,地图基于二维占用栅格。使用Dempster-Shafer推理规则将传感器读数“融合”到地图中。这种具有多值假设的证据方法可以对数据质量进行定量分析。使用来自真实环境的声纳数据对地图构建系统进行实验评估。

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