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Opportunistic Multi-sensor Fusion for Robust Navigation in Smart Environments

机译:在智能环境中进行稳健导航的机会多传感器融合

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This paper presents the design of a navigation system for multiple autonomous robotic platforms. It performs multisensor fusion using a Monte Carlo Bayesian filter, and has been designed to maximize information acquisition. Apart from sensors equipped in the mobile platform, the system can dynamically integrate observations from friendly external sensing entities, increasing robustness and making it suitable for both indoor and outdoor operation. A multi-agent layer manages the information acquisition process, making it transparent for the core filtering solution. As a proof of concept, some preliminary results are presented over a real platform using the part of the system specialized in outdoor navigation.
机译:本文介绍了用于多个自主机器人平台的导航系统的设计。它使用蒙特卡洛贝叶斯滤波器执行多传感器融合,并且已被设计为最大化信息获取。除了移动平台中配备的传感器之外,该系统还可以动态集成来自友好外部传感实体的观察结果,从而增强了鲁棒性,使其适合于室内和室外操作。多代理层管理信息获取过程,使其对于核心过滤解决方案透明。作为概念验证,使用专门用于户外导航的系统部分,在真实平台上显示了一些初步结果。

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