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Sound Source Localization experiment in variety real environment for intelligent service robots

机译:智能服务机器人在各种真实环境中的声源定位实验

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In this paper, we present a Sound Source Localization (SSL) with robot auditory system for a network-based intelligent service robots that give a service in variety places. The main goal of this paper is to analysis performance of SSL algorithm in real environment for robot. We gathered the sound databases in museum, conference hall and restaurant for SSL experiments. These places will be served by intelligent robot in actually. With using these databases, we compared some of SSL algorithms and searched that we can use the SLL for intelligent robot in real environment. Algorithms for calculating time delay are based on the advanced cross correlation and GCC (Generalized Cross-Correlation)-PHAT(Phase Transform) by frequency characteristics for calculating time delay estimation. The robot platform used in this work is wever-R2, which is a network-based intelligent service robot developed at Intelligent Robot Research Division in ETRI.
机译:在本文中,我们提出了一种基于机器人听觉系统的声源定位(SSL)技术,用于基于网络的智能服务机器人,该机器人可在各种地方提供服务。本文的主要目的是分析真实环境中机器人的SSL算法性能。我们在博物馆,会议厅和餐厅收集了声音数据库,以进行SSL实验。这些地方将由智能机器人实际服务。通过使用这些数据库,我们比较了一些SSL算法,并搜索了我们可以将SLL用于实际环境中的智能机器人。用于计算时间延迟的算法是基于高级互相关和基于频率特性的GCC(广义互相关)-PHAT(相位变换)来计算时间延迟估计的。这项工作中使用的机器人平台是wever-R2,它是由ETRI的智能机器人研究部开发的基于网络的智能服务机器人。

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