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A framework for integrating sensory information in a humanoid robot

机译:在人形机器人中整合感官信息的框架

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摘要

We propose a framework towards the integration of information sensors based on the idea that the stimulus perceived through different sensors are spatial-time correlated for a short time period. Applications in robotics need to be able to process information from multiple sensors, for instance, in the case of a visible talking person. How can we relate this kind of information in a simple way, without making use of high level representation? This is the question that we want to address. A new framework based on a correlation measure of low level data information is proposed. This low level correlation measure can be used as an integration data engine to support high level task description. In the paper a coherent approach from sensor level to task level for developing a robot which can handle a large number of sensors and actuators is developed. An example how this approach can be used for a visual-sound integration task is also presented.
机译:我们提出了一个信息传感器集成的框架,其基础是通过不同传感器感知的刺激在短时间内与时空相关。机器人技术中的应用程序需要能够处理来自多个传感器的信息,例如在有说话能力的人的情况下。我们如何在不使用高级表示的情况下以简单的方式关联此类信息?这是我们要解决的问题。提出了一种基于低层数据信息相关性度量的新框架。此低级相关性度量可用作集成数据引擎,以支持高级任务描述。在本文中,开发了一种从传感器级别到任务级别的一致方法,用于开发可以处理大量传感器和执行器的机器人。还介绍了如何将此方法用于视觉声音集成任务的示例。

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