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Simultaneous Localization of a Mobile Robot and Multiple Sound Sources Using a Microphone Array

机译:使用麦克风阵列同时定位移动机器人和多个声源

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摘要

Sound source localization is an important function in robot audition. Most existing works perform sound source localization using static microphone arrays. This work proposes a framework that simultaneously localizes the mobile robot and multiple sound sources using a microphone array on the robot. First, an eigenstructure-based generalized cross-correlation method for estimating time delays between microphones under multi-source environments is described. Using the estimated time delays, a method to compute the far-field source directions as well as the speed of sound is proposed. In addition, the correctness of the sound speed estimate is utilized to eliminate spurious sources, which greatly enhances the robustness of sound source detection. The arrival angles of the detected sound sources are used as observations in a bearing-only simultaneous localization and mapping procedure. As the source signals are not persistent and there is no identification of the signal content, data association is unknown and it is solved using the FastSLAM algorithm. The experimental results demonstrate the effectiveness of the proposed method.
机译:声源定位是机器人试听的重要功能。现有的大多数作品都使用静态麦克风阵列执行声源定位。这项工作提出了一个框架,该框架使用机器人上的麦克风阵列同时定位移动机器人和多个声源。首先,描述了一种基于特征结构的广义互相关方法,用于估计多源环境下麦克风之间的时间延迟。利用估计的时延,提出了一种计算远场声源方向以及声速的方法。另外,利用声速估计的正确性来消除杂散源,这大大增强了声源检测的鲁棒性。在仅方位同时定位和映射过程中,将检测到的声源的到达角用作观察值。由于源信号不是持久性的,并且没有信号内容的标识,因此数据关联是未知的,可以使用FastSLAM算法解决。实验结果证明了该方法的有效性。

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