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Autonomous Robot Navigation in Human-Centered Environments Based on 3D Data Fusion

机译:基于3D数据融合的以人为本的自主机器人导航

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Efficient navigation of mobile platforms in dynamic human-centered environments is still an open research topic. We have already proposed an architecture (MEPHISTO) for a navigation system that is able to fulfill the main requirements of efficient navigation: fast and reliable sensor processing, extensive global world modeling, and distributed path planning. Our architecture uses a distributed system of sensor processing, world modeling, and path planning units. In this arcticle, we present implemented methods in the context of data fusion algorithms for 3D world modeling and real-time path planning. We also show results of the prototypic application of the system at the museum ZKM (center for art and media) in Karlsruhe.
机译:在以人为中心的动态环境中有效导航移动平台仍然是一个开放的研究主题。我们已经为导航系统提出了一种架构(MEPHISTO),该架构能够满足有效导航的主要要求:快速和可靠的传感器处理,广泛的全球世界建模以及分布式路径规划。我们的体系结构使用传感器处理,世界建模和路径规划单元的分布式系统。在本部分中,我们将在数据融合算法的上下文中介绍用于3D世界建模和实时路径规划的已实现方法。我们还在卡尔斯鲁厄的ZKM博物馆(艺术和媒体中心)展示了该系统的原型应用结果。

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