Distributed management and representation of data and context in robotic applications
Distributed management and representation of data and context in robotic applications
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DOI：
10.1109/iros.2014.6942700
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发表时间：
2014-09
期刊：
影响因子：
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通讯作者：
André Dietrich;Sebastian Zug;Siba Mohammad;J. Kaiser
中科院分区：
文献类型：
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作者：
André Dietrich;Sebastian Zug;Siba Mohammad;J. Kaiser
传感器-执行器系统中传统的孤立数据处理无法满足需要与智能环境交互的机器人的要求。因此，我们必须开发新的自适应数据和上下文处理机制。我们首先研究智能环境中存在哪些类型的数据，以及如何对它们进行分类和组织。只有当可用的数据可以被结构化时，它才可以被查询，从而放入上下文。这一点很重要，因为各种数据和可能的解释是巨大的，从测量值，传感器和机器人的描述/状态/命令，环境数据，如位置，地图，空间关系等，以科普这种多样性，我们开发了一个解决方案，能够存储和访问数据在分布式环境中提供额外的上下文信息。此外，我们描述了这些信息可以组装在一个面向任务的方式。这使机器人能够通过使用来自不同来源的数据动态生成环境抽象，并使它们能够结合外部传感器测量。
The traditional, isolated data handling in sensor-actuator systems does not fulfill the requirements of robots that need to interact with their smart environment. Consequently, we have to develop new mechanisms for adaptive data and context handling. We firstly investigate what types of data are present within smart environments and how they can be classified and organized. Only if the available data can be structured, it can be queried and thus put into context. This is important because the variety of data and possible interpretations is tremendous, ranging from measurement values, sensor and robot descriptions/states/commands, to environmental data, such as positions, maps, spatial relations, etc. To cope with this diversity, we developed a solution capable of storing and accessing data within a distributed environment by providing additional context information. Furthermore, we describe how this information can be assembled in a task-oriented manner. This enables robots to dynamically generate environmental abstractions by using data from different sources and also enables them to incorporate external sensor measurements.