318 research outputs found
POSITION CALIBRATION OF ACOUSTIC SENSORS AND ACTUATORS ON DISTRIBUTED GENERAL PURPOSE COMPUTING PLATFORMS
An algorithm is presented to automatically determine the relative 3D positions of audio sensors and actuators in an ad-hoc distributed network of heterogeneous general purpose computing platforms. A closed form approximate solution is derived, which is further refined by minimizing a non-linear error function. Our formulation and solution accounts for the lack of temporal synchronization among different platforms. We also derive an approximate expression for the mean and covariance of the implicitly defined estimator. The theoretical performance limits for the sensor positions are derived and analyzed with respect to the number of sensors and actuators as well as their geometry. We report extensive simulation results and discuss the practical details of implementing our algorithms
Ad Hoc Microphone Array Calibration: Euclidean Distance Matrix Completion Algorithm and Theoretical Guarantees
This paper addresses the problem of ad hoc microphone array calibration where
only partial information about the distances between microphones is available.
We construct a matrix consisting of the pairwise distances and propose to
estimate the missing entries based on a novel Euclidean distance matrix
completion algorithm by alternative low-rank matrix completion and projection
onto the Euclidean distance space. This approach confines the recovered matrix
to the EDM cone at each iteration of the matrix completion algorithm. The
theoretical guarantees of the calibration performance are obtained considering
the random and locally structured missing entries as well as the measurement
noise on the known distances. This study elucidates the links between the
calibration error and the number of microphones along with the noise level and
the ratio of missing distances. Thorough experiments on real data recordings
and simulated setups are conducted to demonstrate these theoretical insights. A
significant improvement is achieved by the proposed Euclidean distance matrix
completion algorithm over the state-of-the-art techniques for ad hoc microphone
array calibration.Comment: In Press, available online, August 1, 2014.
http://www.sciencedirect.com/science/article/pii/S0165168414003508, Signal
Processing, 201
Implementation of an Autonomous Impulse Response Measurement System
Data collection is crucial for researchers, as it can provide important insights for describing phenomena. In acoustics, acoustic phenomena are characterized by Room Impulse Responses (RIRs) occurring when sound propagates in a room. Room impulse responses are needed in vast quantities for various reasons, including the prediction of acoustical parameters and the rendering of virtual acoustical spaces. Recently, mobile robots navigating within indoor spaces have become increasingly used to acquire information about its environment. However, little research has attempted to utilize robots for the collection of room acoustic data.
This thesis presents an adaptable automated system to measure room impulse responses in multi-room environments, using mobile and stationary measurement platforms. The system, known as Autonomous Impulse Response Measurement System (AIRMS), is divided into two stages: data collection and post-processing. To automate data collection, a mobile robotic platform was developed to perform acoustic measurements within a room. The robot was equipped with spatial microphones, multiple loudspeakers and an indoor localization system, which reported real time location of the robot. Additionally, stationary platforms were installed in specific locations inside and outside the room. The mobile and stationary platforms wirelessly communicated with one another to perform the acoustical tests systematically. Since a major requirement of the system is adaptability, researchers can define the elements of the system according to their needs, including the mounted equipment and the number of platforms. Post-processing included extraction of sine sweeps and the calculation of impulse responses. Extraction of the sine sweeps refers to the process of framing every acoustical test signal from the raw recordings. These signals are then processed to calculate the room impulse responses. The automatically collected information was complemented with manually produced data, which included rendering of a 3D model of the room, a panoramic picture.
The performance of the system was tested under two conditions: a single-room and a multiroom setting. Room impulse responses were calculated for each of the test conditions, representing typical characteristics of the signals and showing the effects of proximity from sources and receivers, as well as the presence of boundaries. This prototype produces RIR measurements in a fast and reliable manner.
Although some shortcomings were noted in the compact loudspeakers used to produce the sine sweeps and the accuracy of the indoor localization system, the proposed autonomous measurement system yielded reasonable results. Future work could expand the amount of impulse response measurements in order to further refine the artificial intelligence algorithms
Simultaneous ranging and self-positioning in unsynchronized wireless acoustic sensor networks
Automatic ranging and self-positioning is a very
desirable property in wireless acoustic sensor networks (WASNs)
where nodes have at least one microphone and one loudspeaker.
However, due to environmental noise, interference and multipath
effects, audio-based ranging is a challenging task. This paper
presents a fast ranging and positioning strategy that makes use
of the correlation properties of pseudo-noise (PN) sequences for
estimating simultaneously relative time-of-arrivals (TOAs) from
multiple acoustic nodes. To this end, a proper test signal design
adapted to the acoustic node transducers is proposed. In addition,
a novel self-interference reduction method and a peak matching
algorithm are introduced, allowing for increased accuracy in
indoor environments. Synchronization issues are removed by
following a BeepBeep strategy, providing range estimates that
are converted to absolute node positions by means of multidimensional
scaling (MDS). The proposed approach is evaluated both
with simulated and real experiments under different acoustical
conditions. The results using a real network of smartphones and
laptops confirm the validity of the proposed approach, reaching
an average ranging accuracy below 1 centimeter.This work was supported by the Spanish Ministry of Economy and Competitiveness under Grant TIN2015-70202-P, TEC2012-37945-C02-02 and FEDER funds
Blind as a bat: audible echolocation on small robots
For safe and efficient operation, mobile robots need to perceive their
environment, and in particular, perform tasks such as obstacle detection,
localization, and mapping. Although robots are often equipped with microphones
and speakers, the audio modality is rarely used for these tasks. Compared to
the localization of sound sources, for which many practical solutions exist,
algorithms for active echolocation are less developed and often rely on
hardware requirements that are out of reach for small robots. We propose an
end-to-end pipeline for sound-based localization and mapping that is targeted
at, but not limited to, robots equipped with only simple buzzers and low-end
microphones. The method is model-based, runs in real time, and requires no
prior calibration or training. We successfully test the algorithm on the e-puck
robot with its integrated audio hardware, and on the Crazyflie drone, for which
we design a reproducible audio extension deck. We achieve centimeter-level wall
localization on both platforms when the robots are static during the
measurement process. Even in the more challenging setting of a flying drone, we
can successfully localize walls, which we demonstrate in a proof-of-concept
multi-wall localization and mapping demo.Comment: 8 pages, 10 figures, published in IEEE Robotics and Automation
Letter
Localization of sound sources : a systematic review
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 use
Enhanced Diffuse Field Model for Ad Hoc Microphone Array Calibration
In this paper, we investigate the diffuse field coherence model for microphone array pairwise distance estimation. We study the fundamental constraints and assumptions underlying this approach and propose evaluation methodologies to measure the adequacy of diffuseness for microphone array calibration. In addition, an enhanced scheme based on coherence averaging and histogramming, is presented to improve the robustness and performance of the pairwise distance estimation approach. The proposed theories and algorithms are evaluated on simulated and real data recordings for calibration of microphone array geometry in an ad hoc set-up
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