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Storing and retrieving perceptual episodic memories for long-term manipulation tasks

机译:存储和检索感知性情景记忆以进行长期操作

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With recent technological advances, robotic agents are increasingly capable of performing ever more sophisticated manipulation tasks. Perceptual capabilities of these robots need to be able to adapt to the wide variety of tasks they are to perform. Remembering what a robot has seen, what the rationale was behind the decisions it took or how it ended up understanding the world as it did, are important questions if we want perception capabilities that can scale towards real-world manipulation. We present a robotic perception system that generates perceptual episodic memories during the execution of a task. To allow easy retrieval of these memories we introduce an object and scene description language that serves as a layer of abstraction between the structure of the perception logs and the semantic interpretation of these. The description language can be used through a query interface to retrieve specific parts of the generated episodic memory. The purpose of the proposed system is two-fold: to enable on-line retrospection and specialized training of perception routines and to enable researchers to interactively explore perception results.
机译:随着最新技术的进步,机器人代理越来越有能力执行越来越复杂的操纵任务。这些机器人的感知能力需要能够适应他们要执行的各种各样的任务。如果我们想让感知能力能够朝着现实世界的方向发展,那么记住机器人所看到的东西,做出决定的依据是什么,或者它最终如何像过去那样理解世界是很重要的问题。我们提出了一种机器人感知系统,该机器人在执行任务期间会产生感知性的情节性记忆。为了便于检索这些内存,我们引入了一种对象和场景描述语言,该语言充当感知日志的结构与这些语义的语义解释之间的抽象层。可以通过查询界面使用描述语言来检索生成的情节记忆的特定部分。拟议系统的目的有两个:使在线回顾和感知程序的专门训练成为可能,并使研究人员能够交互式地探索感知结果。

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