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Performance Bounds for Cooperative Simultaneous Localization and Mapping (C-SLAM)

机译:协作同时定位和制图(C-SLAM)的性能界限

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In this paper we study the time evolution of the position estimates' covariance in Cooperative Simultaneous Localization and Mapping (C-SLAM), and obtain analytical upper bounds for the positioning uncertainty. The derived bounds provide descriptions of the asymptotic positioning performance of a team of robots in a mapping task, as a function of the characteristics of the proprioceptive and exteroceptive sensors of the robots, and of the graph of relative position measurements recorded by the robots. A study of the properties of the Riccati recursion which describes the propagation of uncertainty through time, yields (ⅰ) the guaranteed accuracy for a robot team in a given C-SLAM application, as well as (ⅱ) the maximum expected steady-state uncertainty of the robots and landmarks, when the spatial distribution of features in the environment can be modeled by a known distribution. The theoretical results are validated by simulation experiments.
机译:在本文中,我们研究了协作同时定位与制图(C-SLAM)中位置估计协方差的时间演化,并获得了定位不确定性的解析上限。导出的边界提供了一组机器人在映射任务中的渐近定位性能的描述,这些性能取决于机器人的本体感受和本体感受传感器的特性以及由机器人记录的相对位置测量图。研究Riccati递归的属性,该属性描述了不确定性随时间的传播,得出(ⅰ)在给定的C-SLAM应用中机器人团队的保证精度,以及(the)最大预期稳态不确定性当可以通过已知分布来模拟环境中要素的空间分布时,就可以使用机器人和地标。通过仿真实验验证了理论结果。

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