Sound Localization and Separation for Mobile Robot Tele-Operation by Tri-Concentric Microphone Array

2007 ◽  
Vol 19 (3) ◽  
pp. 281-289 ◽  
Author(s):  
Yoko Sasaki ◽  
◽  
Saori Masunaga ◽  
Simon Thompson ◽  
Satoshi Kagami ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Auditory System ◽  
Sound Localization ◽  
Source Localization ◽  
Microphone Array ◽  
Visual Presentation ◽  
Sound Source Localization ◽  
Robot System ◽  
Sound Sources

The paper describes a tele-operated mobile robot system which can perform multiple sound source localization and separation using a 32-channel tri-concentric microphone array. Tele-operated mobile robots require two main capabilities: 1) audio/visual presentation of the robot’s environment to the operator, and 2) autonomy for mobility. This paper focuses on the auditory system of a tele-operated mobile robot in order to improve both the presentation of sound sources to the operator and also to facilitate autonomous robot actions. The auditory system is based on a 32-channel distributed microphone array that uses highly efficient directional design for localizing and separating multiple moving sound sources. Experimental results demonstrate the feasibility of inter-person distant communication through the tele-operated robot system.

Phase calibration method for microphone array based on multiple sound sources

2021 ◽  
Vol 263 (6) ◽  
pp. 659-669
Author(s):  
Bo Jiang ◽  
XiaoQin Liu ◽  
Xing Wu
Keyword(s):  
Nonlinear Equation ◽  
Source Localization ◽  
Sound Source ◽  
Microphone Array ◽  
Phase Error ◽  
Phase Mismatch ◽  
Single Frequency ◽  
Sound Source Localization ◽  
Sound Sources ◽  
Error Calibration

In the microphone array, the phase error of each microphone causes a deviation in sound source localization. At present, there is a lack of effective methods for phase error calibration of the entire microphone array. In order to solve this problem, a phase mismatch calculation method based on multiple sound sources is proposed. This method requires collecting data from multiple sound sources in turn, and constructing a nonlinear equation setthrough the signal delay and the geometric relationship between the microphones and the sound source positions. The phase mismatch of each microphone can be solved from the nonlinear equation set. Taking the single frequency signal as an example, the feasibility of the method is verified by experiments in a semi-anechoic chamber. The phase mismatches are compared with the calibration results of exchanging microphone. The difference of the phase error values measured by the two methods is small. The experiment also shows that the accuracy of sound source localization by beamforming is improved. The method is efficient for phase error calibration of arrays with a large number of microphones.

Influence of Different Impulse Response Measurement Signals on MUSIC-Based Sound Source Localization

2017 ◽  
Vol 29 (1) ◽  
pp. 72-82 ◽  
Author(s):  
Takuya Suzuki ◽  
◽  
Hiroaki Otsuka ◽  
Wataru Akahori ◽  
Yoshiaki Bando ◽  
...  
Keyword(s):  
Impulse Response ◽  
Source Localization ◽  
Sound Source ◽  
Transfer Functions ◽  
Signal To Noise Ratio ◽  
Microphone Array ◽  
Sound Source Localization ◽  
Sound Sources ◽  
Response Measurement ◽  
Significant Difference

[abstFig src='/00290001/07.jpg' width='300' text='Six impulse response measurement signals' ] Two major functions, sound source localization and sound source separation, provided by robot audition open source software HARK exploit the acoustic transfer functions of a microphone array to improve the performance. The acoustic transfer functions are calculated from the measured acoustic impulse response. In the measurement, special signals such as Time Stretched Pulse (TSP) are used to improve the signal-to-noise ratio of the measurement signals. Recent studies have identified the importance of selecting a measurement signal according to the applications. In this paper, we investigate how six measurement signals – up-TSP, down-TSP, M-Series, Log-SS, NW-SS, and MN-SS – influence the performance of the MUSIC-based sound source localization provided by HARK. Experiments with simulated sounds, up to three simultaneous sound sources, demonstrate no significant difference among the six measurement signals in the MUSIC-based sound source localization.

scholarly journals DESIGNING PLANAR MICROPHONE ARRAY FOR SOUND SOURCE LOCALIZATION

Akustika ◽  
2019 ◽  
Vol 32 ◽  
pp. 123-129 ◽  
Author(s):  
Victor Ershov ◽  
Vadim Palchikovskiy
Keyword(s):  
Inclination Angle ◽  
Source Localization ◽  
Sound Source ◽  
Dynamic Range ◽  
Microphone Array ◽  
Sound Source Localization ◽  
Maximum Diameter ◽  
Design Parameters ◽  
Sound Sources ◽  
The Individual

Mathematical background for designing planar microphone array for localization of sound sources are described shortly. The designing is based on optimization of objective function, which is maximum dynamic range of sound source localization. The design parameters are radial coordinates (distance along the beam from the center of the array) and angle coordinates (beam inclination) of the microphones. It is considered the arrays with the same radial coordinates of the microphones for each beam and the independent radial coordinates of each microphone, as well as the same inclination angle for all beams and the individual inclination angle of each beam. As constraints, it is used the minimum allowable distance between two adjacent microphones, and minimum and maximum diameter of the working area of the array. The solution of the optimization problem is performed by the Minimax method. An estimation of the resolution quality of designed arrays was carried out based on localization of three monopole sources. The array of 3 m in diameter without inclination of the beams and with different radial coordinates of the microphones on each beam was found to be the most efficient configuration among the considered ones.

scholarly journals Binaural Signal Integration Improves Vertical Sound Source Localization

2020 ◽  
Author(s):  
Timo Oess ◽  
Heiko Neumann ◽  
Marc O. Ernst
Keyword(s):  
Auditory System ◽  
Source Localization ◽  
Sound Source ◽  
Prior Information ◽  
Vertical Plane ◽  
Sound Source Localization ◽  
Signal Integration ◽  
Sound Sources ◽  
Localization Performance ◽  
Monaural Spectral Cues

AbstractEarly studies have shown that the localization of a sound source in the vertical plane can be accomplished with only a single ear and thus assumed to be based on monaural spectral cues. Such cues consists of notches and peaks in the perceived spectrum which vary systematically with the elevation of sound sources. This poses several problems to the auditory system like extracting relevant and direction-dependent cues among others. Interestingly, at the stage of elevation estimate binaural information from both ears is already available and it seems reasonable of the auditory system to take advantage of this information. Especially, since such a binaural integration can improve the localization performance dramatically as we demonstrate with a computational model of binaural signal integration for sound source localization in the vertical plane. In line with previous findings of vertical localization, modeling results show that the auditory system can perform monaural as well as binaural sound source localization given a single, learned map of binaural signals. Binaural localization is by far more accurate than monaural localization, however, when prior information about the perceived sound is integrated localization performance is restored. Thus, we propose that elevation estimation of sound sources is facilitated by an early binaural signal integration and can incorporate sound type specific prior information for higher accuracy.

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