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

2011 ◽  
Vol 25 (1-2) ◽  
pp. 135-152 ◽  
Author(s):  
Jwu-Sheng Hu ◽  
Chen-Yu Chan ◽  
Cheng-Kang Wang ◽  
Ming-Tang Lee ◽  
Ching-Yi Kuo
Keyword(s):  
Mobile Robot ◽  
Microphone Array ◽  
Sound Sources

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.

Pitch-Cluster-Map Based Daily Sound Recognition for Mobile Robot Audition

2010 ◽  
Vol 22 (3) ◽  
pp. 402-410 ◽  
Author(s):  
Yoko Sasaki ◽  
◽  
Masahito Kaneyoshi ◽  
Satoshi Kagami ◽  
Hiroshi Mizoguchi ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Microphone Array ◽  
Recognition Performance ◽  
Source Tracking ◽  
Sound Recognition ◽  
Recognition Method ◽  
Short Term ◽  
Sound Sources ◽  
Robot Audition ◽  
Office Environments

This paper presents a sound identification method for a mobile robot in home and office environments. We propose a short-term sound recognition method using Pitch-Cluster-Maps (PCMs) sound database (DB) based on a Vector Quantization approach. A binarized frequency spectrum is used to generate PCMs codebook, which describes a variety of sound sources, not only voice, from short-term sound input. PCMs sound identification requires several tens of milliseconds of sound input, and is suitable for mobile robot applications in which conditions are continuously and dynamically changing. We implemented this in mobile robot audition system using a 32-channel microphone array. Robot noise reduction and sound source tracking using our proposal are applied to robot audition system, and we evaluate daily sound recognition performance for separated sound sources from a moving robot.

scholarly journals Visual Representation of Sound Sources and Interaction Forces in a Teleoperation Interface for a Mobile Robot

2015 ◽  
Vol 4 (2) ◽  
pp. 1 ◽  
Author(s):  
Aurélien Reveleau ◽  
François Ferland ◽  
Mathieu Labbé ◽  
Dominic Létourneau ◽  
François Michaud
Keyword(s):  
Mobile Robot ◽  
Visual Representation ◽  
Sound Sources ◽  
Interaction Forces

Locating and tracking sound sources on a horizontal axis wind turbine using a compact microphone array based on beamforming

2019 ◽  
Vol 146 ◽  
pp. 295-309 ◽  
Author(s):  
Cui Qing Zhang ◽  
Zhi Ying Gao ◽  
Yong Yan Chen ◽  
Yuan Jun Dai ◽  
Jian Wen Wang ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Microphone Array ◽  
Horizontal Axis ◽  
Horizontal Axis Wind Turbine ◽  
Sound Sources

Layout Optimization of Cooperative Distributed Microphone Arrays Based on Estimation of Source Separation Performance

2017 ◽  
Vol 29 (1) ◽  
pp. 83-93
Author(s):  
Kouhei Sekiguchi ◽  
◽  
Yoshiaki Bando ◽  
Katsutoshi Itoyama ◽  
Kazuyoshi Yoshii
Keyword(s):  
Mobile Robots ◽  
Microphone Array ◽  
Source Separation ◽  
Microphone Arrays ◽  
Separation Performance ◽  
Sound Sources ◽  
Multiple Mobile Robots ◽  
Position Information ◽  
Reconfigurable Array ◽  
Source Signals

[abstFig src='/00290001/08.jpg' width='300' text='Optimizing robot positions for source separation' ] The active audition method presented here improves source separation performance by moving multiple mobile robots to optimal positions. One advantage of using multiple mobile robots that each has a microphone array is that each robot can work independently or as part of a big reconfigurable array. To determine optimal layout of the robots, we must be able to predict source separation performance from source position information because actual source signals are unknown and actual separation performance cannot be calculated. Our method thus simulates delay-and-sum beamforming from a possible layout to calculate gain theoretically, i.e., the expected ratio of a target sound source to other sound sources in the corresponding separated signal. Robots are moved into the layout with the highest average gain over target sources. Experimental results showed that our method improved the harmonic mean of signal-to-distortion ratios (SDRs) by 5.5 dB in simulation and by 3.5 dB in a real environment.

Sign in / Sign up

Export Citation Format

Share Document