异步多中心协作定位

Esha D. Nerurkar, S. Roumeliotis
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引用次数: 32

摘要

本文提出了异步通信条件下,即与移动机器人网络相关联的通信图时变且间歇断开时,多中心化协同定位(MC-CL)中机器人间信息传递方案的广义框架。具体地说,讨论了两种基于每链路通信带宽要求不同的信息传输方案。即使在异步通信约束下,这些方案也使机器人能够计算出与使用集中式CL框架生成的相同的姿态估计,尽管延迟了。对于每种方案,给出了通信图连通性的充分必要条件,使每个机器人能够产生集中的估计。此外,还详细描述了这些方案,以及它们的通信复杂度分析和获得这些估计的期望时延的分析结果。最后,用仿真结果验证了这些信息传输方案的性能(通信链路带宽和精度/延迟之间的权衡)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Asynchronous Multi-Centralized Cooperative Localization
This paper presents a generalized framework for inter-robot information-transfer schemes in Multi-Centralized Cooperative Localization (MC-CL) under asynchronous communication, i.e., when the communication graph associated with the mobile robot network is time-varying and intermittently disconnected. Specifically, two information-transfer schemes, which differ based on their communication bandwidth requirements per link, are discussed. Even under asynchronous communication constraints, these schemes enable robots to compute pose estimates identical to those generated using the centralized CL framework, albeit delayed. For each of these schemes, necessary and sufficient conditions for the communication-graph connectivity, that enable each robot to generate the centralized estimates, are developed. Moreover, detailed description of these schemes, along with their communication-complexity analysis and analytical results for the expected time delay in obtaining these estimates, are presented. Lastly, simulation results are used to validate the performance (the trade-off between communication link bandwidth and accuracy/delay) of these information-transfer schemes.
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