Design and Assessment of Sound Source Localization System with a UAV-Embedded Microphone Array

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018

This paper introduces DREGON, a novel publiclyavailable dataset that aims at pushing research in sound source localization using a microphone array embedded in an unmanned aerial vehicle (UAV). The dataset contains both clean and noisy in-flight audio recordings continuously annotated with the 3D position of the target sound source using an accurate motion capture system. In addition, various signals of interests are available such as the rotational speed of individual rotors and inertial measurements at all time. Besides introducing the dataset, this paper sheds light on the specific properties, challenges and opportunities brought by the emerging task of UAV-embedded sound source localization. Several baseline methods are evaluated and compared on the dataset, with real-time applicability in mind. Very promising results are obtained for the localization of a broad-band source in loud noise conditions, while speech localization remains a challenge under extreme noise levels.

Journal of Intelligent & Robotic Systems

This work presents a novel technique that performs both orientation and distance localization of a sound source in a three-dimensional (3D) space using only the interaural time difference (ITD) cue, generated by a newly-developed self-rotational bi-microphone robotic platform. The system dynamics is established in the spherical coordinate frame using a state-space model. The observability analysis of the state-space model shows that the system is unobservable when the sound source is placed with elevation angles of 90 and 0 degree. The proposed method utilizes the difference between the azimuth estimates resulting from respectively the 3D and the two-dimensional models to check the zero-degreeelevation condition and further estimates the elevation angle using a polynomial curve fitting approach. Also, the proposed method is capable of detecting a 90-degree elevation by extracting the zero-ITD signal 'buried' in noise. Additionally, a distance localization is performed by first rotating the microphone array to face toward the sound source and then shifting the microphone perpendicular to the source-robot vector by a predefined distance of a fixed number of steps. The integrated rotational and translational motions of the microphone array provide a complete orientation and distance localization using only the ITD cue. A novel robotic platform using a self-rotational bi-microphone array was also developed for unmanned ground robots performing sound source localization. The proposed technique was first tested in simulation and was then verified on the newly-developed robotic platform. Experimental data collected by the microphones installed on a KEMAR Deepak Gala,

ArXiv, 2018

While vision-based localization techniques have been widely studied for small autonomous unmanned vehicles (SAUVs), sound-source localization capability has not been fully enabled for SAUVs. This paper presents two novel approaches for SAUVs to perform multi-sound-sources localization (MSSL) using only the interaural time difference (ITD) signal generated by a self-rotating bi-microphone array. The proposed two approaches are based on the DBSCAN and RANSAC algorithms, respectively, whose performances are tested and compared in both simulations and experiments. The results show that both approaches are capable of correctly identifying the number of sound sources along with their three-dimensional orientations in a reverberant environment.

2013

Sound source localization in real time can be employed in numerous applications such as filtering, beamforming, security system integration, etc. Algorithms employed in this field require not only fast processing speed but also enough accuracy to properly cope with the application requirements. This work presents accuracy benchmarks of a hybrid approach previously proposed, which is based on the Generalized Cross Correlation (GCC), and the Delay and Sum beamforming (DSB). Tests were performed considering a linear microphone array simulated in MATLAB. Analysis through variations in array size, number of microphones, spacing and other characteristics, were included. Results obtained show that the proposed algorithm is as good as the DSB under some conditions that can be easily met.

Energies

Sound localization is a vast field of research and advancement which is used in many useful applications to facilitate communication, radars, medical aid, and speech enhancement to but name a few. Many different methods are presented in recent times in this field to gain benefits. Various types of microphone arrays serve the purpose of sensing the incoming sound. This paper presents an overview of the importance of using sound localization in different applications along with the use and limitations of ad-hoc microphones over other microphones. In order to overcome these limitations certain approaches are also presented. Detailed explanation of some of the existing methods that are used for sound localization using microphone arrays in the recent literature is given. Existing methods are studied in a comparative fashion along with the factors that influence the choice of one method over the others. This review is done in order to form a basis for choosing the best fit method for our...

International Journal of Advanced Research in Electrical, Electronics and Instrumentation Energy, 2013

Source Localization is a very well established technique that has a wide range of applications from remote sensing to the Global Positioning System. Sound source localization techniques are used in commercial applications like improving speech quality in hands free telephony, video conferencing to military applications like SONAR, surveillance systems and devices to locate the sources of artillery fire. A method is proposed to localize an acoustic source within a frequency band from 100Hz to 4 KHz in two dimensions using microphone array by calculating the direction of arrival (DOA) of the acoustic signals. Direction of arrival (DOA) estimation of acoustic signals using a set of spatially separated microphones uses the phase information present in signals. For this the time-delays are estimated for each pair of microphones in the array. From the known array geometry and the direction of arrival, the location of source can be obtained.

In this paper, we present a robust real-time sound source localization system implemented on a social robot platform developed in Institute for Infocomm Research, Singapore. The audio localization system provides the robot with auditory senses and enables the robot to direct its face to a speaker outside its frontal vision system. As the localization system exploits time difference of arrival (TDOA), the placement of the 8 microphone system array is crucial. This paper discusses the configuration and implementation of our system for the Olivia robot platform for accurate 3D localization under high babble noise condition. 10-0101490152©2010 APSIPA. All rights reserved.

Video conference systems have been widely used. A fix video camera shoots a scene is lacking in changes. There is a method that the computer-controlled camera shoots and finds the sound source. Microphone arrays and distributed microphone arrays are used to localize the sound source based on time delay of arrival (TDOA). In order to minimize the error rate of TDOA, a set of 4 microphone arrays can be used to determine the location of sound in 3D space. TDOA cannot determine the distance of the sound source if the start time of the sound is unknown. A method to determine the distance of the sound source is using a distributed moving-microphone array. In this paper, we propose a model of a set of 4 moving-micorphone array based on TDOA that can determine the angle direction and distance of the sound source toward the video camera at the center of the model in 3D space.

Robotics and Autonomous Systems, 2019

Human-robot interaction in natural settings requires filtering out the different sources of sounds from the environment. Such ability usually involves the use of microphone arrays to localize, track and separate sound sources online. Multimicrophone signal processing techniques can improve robustness to noise but the processing cost increases with the number of microphones used, limiting response time and widespread use on different types of mobile robots. Since sound source localization methods are the most expensive in terms of computing resources as they involve scanning a large 3D space, minimizing the amount of computations required would facilitate their implementation and use on robots. The robot's shape also brings constraints on the microphone array geometry and configurations. In addition, sound source localization methods usually return noisy features that need to be smoothed and filtered by tracking the sound sources. This paper presents a novel sound source localization method, called SRP-PHAT-HSDA, that scans space with coarse and fine resolution grids to reduce the number of memory lookups. A microphone directivity model is used to reduce the number of directions to scan and ignore non significant pairs of microphones. A configuration method is also introduced to automatically set parameters that are normally empirically tuned according to the shape of the microphone array. For sound source tracking, this paper presents a modified 3D Kalman (M3K) method capable of simultaneously tracking in 3D the directions of sound sources. Using a 16-microphone array and low cost hardware, results show that SRP-PHAT-HSDA and M3K perform at least as well as other sound source localization and tracking methods while using up to 4 and 30 times less computing resources respectively.

Robotics and Autonomous Systems, 2017

Sound source localization (SSL) in a robotic platform has been essential in the overall scheme of robot audition. It allows a robot to locate a sound source by sound alone. It has an important impact on other robot audition modules, such as source separation, and it enriches human–robot interaction by complementing the robot's perceptual capabilities. The main objective of this review is to thoroughly map the current state of the SSL field for the reader and provide a starting point to SSL in robotics. To this effect, we present: the evolution and historical context of SSL in robotics; an extensive review and classification of SSL techniques and popular tracking methodologies; different facets of SSL as well as its state-of-the-art; evaluation methodologies used for SSL; and a set of challenges and research motivations.

—In this paper, we have chronicled the development of sound localization system based on TDOA (Time Difference of Arrival). Acoustic Source Localization (ASL) is a technique used to track and locate the exact location of a sound source using an array of microphones. The concept of ASL uses sound signals captured from an array of microphones and they are processed using TDOA localization method to estimate the probable direction of sound source w.r.t to the microphone location. TDOA algorithm is a time delay estimation technique which estimates the time difference in the signal received at each microphone pair. These time delays obtained are then used in the Linear Least Squares (LSQR) Algorithm to estimate the source position w.r.t the microphone array. This system is implemented in real-time by using an on-board DSP processor TMS320C6748.

A possible algorithm for sound source localization in a security system that is based on beamforming of a microphone array is described in this paper. It is shown that the adaptive beamforming algorithm, Minimum Variance Distortionless Response (MVDR), can be a part of the signal processing implemented in a security system. This signal processing includes the following stages: sound source localization, signal parameter estimation, signal priority analysis and, finally, control of protective and warning means (for example, video camera). The adaptive beamforming method MVDR is used for estimating the direction-of arrival (DOA) of signals generated by different sound sources, which arrive at the microphone array from different directions of the protected area. The scenario, in which four sound sources located at different points of the protected area generate different sound signals (warning, alarm, emergency and natural noise), is simulated in order to verify the algorithm for DOA estimation. The simulation results show that an adaptive microphone array can be successfully used for accurate localization of all sound sources in the observation area. The parallel version of the described algorithm is tested in Blue Gene environment using the interface MPI.

Proceedings of the 5th International Conference of Control, Dynamic Systems, and Robotics (CDSR'18), 2018

This paper presents a novel three-dimensional (3D) sound source localization (SSL) technique based on only Interaural Time Difference (ITD) signals, acquired by a self-rotational two-microphone array on an Unmanned Ground Vehicle. Both the azimuth and elevation angles of a stationary sound source are identified using the phase angle and amplitude of the acquired ITD signal. An SSL algorithm based on an extended Kalman filter (EKF) is developed. The observability analysis reveals the singularity of the state when the sound source is placed above the microphone array. A means of detecting this singularity is then proposed and incorporated into the proposed SSL algorithm. The proposed technique is tested in both a simulated environment and two hardware platforms, i.e., a KEMAR dummy binaural head and a robotic platform. All results show the fast and accurate convergence of estimates.

2012

The performance of sound source localization systems based on microphone arrays is dictated by a combination of factors that range from array, source, and environmental characteristics to the nature of the localization algorithm itself. Array geometry is an example of critical feature for source localizability. This paper proposes a numerical measure of the capability of a microphone array with a specific geometry to distinguish a given point in space from its neighbors. Such numerical measure, herein called discriminability index (D), has the interesting feature of taking into account only the effects of array geometry on spatial resolution, thus providing a way of connecting a microphone array geometry to the region of interest. The proposed measure can be particularly useful to help choose an appropriate array geometry when a sound source is confined to a predefined region. Simulation results using the classic SRP-PHAT method are presented for highlighting the correlation between D and the accuracy of the source location estimates.

2009

Paper deals with acoustic source localization using microphone array using time-delay estimation method. It describes main requirements, hardware design of the microphone units with automatic gain control preamplifiers with integrated anti-aliasing filters and finally its connection to standard personal computer equipped with Advantech PCI-1716 multifunction data acquisition card. Next part of the paper describes time-delay estimation method of the direction of arrival of the sound wave and its software implementation for real-time evaluation. Created software application for audio data analysis and direction of arrival computations provides user-friendly graphical user interface which is able to visualize recorded sound waves and frequency spectra in sound analyzer mode and direction of arrival of sound wave in locator mode. All acquired data from microphone units can be saved to the standard user specifiable wav files for further investigation and analysis.