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Simultaneous Estimation of Position and Orientation for Multi-Robot Systems without Compass

机译:没有指南针的多机器人系统的立场和方向同时估计

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This paper investigates the posture localization problem (simultaneously estimating the positions and orientations) for multi-robot systems with relative position measurements in their own local frames. It is assumed that none of the robots has access to a compass and knows the difference of its local frame relative to the global frame. Under such a setup, this paper shows that the solvability of the posture localization problem is equivalent to the joint localizability of estimating only positions, and moreover, it is also equivalent to a very simple graphical condition that each connected component contains at least two anchors. In addition, this paper explores self-localizable, jointly localizable, and unlocalizable conditions and provides a classification algorithm in a self-evaluation manner. Finally, corresponding to different categories of robots, heterogeneous distributed iteration algorithms are presented, which can globally asymptotically solve for true positions and orientations simultaneously. Simulation validates the proposed distributed algorithms.
机译:本文调查了在其自己的本地框架中具有相对位置测量的多机器人系统的姿势定位问题(同时估计位置和方向)。假设没有一个机器人可以访问指南针并知道其本地帧相对于全局帧的差异。在这种设置下,本文表明,姿势定位问题的可解性等同于估计位置的关节定位,而且还等同于每个连接部件至少两个锚点的非常简单的图形条件。此外,本文探讨了自定义,共同定位和无差异条件,并以自我评估方式提供分类算法。最后,对应于不同类别的机器人,呈现异构分布式迭代算法,其可以同时全局渐近地渐近真实位置和取向。仿真验证所提出的分布式算法。

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