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Robotics and Autonomous Systems
Article . 2017 . Peer-reviewed
License: CC BY
Data sources: Crossref
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
Robotics and Autonomous Systems
Article
License: CC BY
Data sources: UnpayWall
https://dx.doi.org/10.60692/p6...
Other literature type . 2017
Data sources: Datacite
https://dx.doi.org/10.60692/hn...
Other literature type . 2017
Data sources: Datacite
DBLP
Article . 2017
Data sources: DBLP
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Localization of sound sources in robotics: A review

توطين مصادر الصوت في الروبوتات: مراجعة
Authors: Caleb Rascón; Iván Meza;

Localization of sound sources in robotics: A review

Abstract

La localisation de la source sonore (SSL) dans une plate-forme robotique a été essentielle dans le schéma global de l'audition du robot. Il permet à un robot de localiser une source sonore uniquement par le son. Il a un impact important sur d'autres modules d'audition de robot, tels que la séparation des sources, et il enrichit l'interaction homme-robot en complétant les capacités perceptives du robot. L'objectif principal de cette revue est de cartographier en profondeur l'état actuel du champ SSL pour le lecteur et de fournir un point de départ à SSL en robotique. À cet effet, nous présentons : l'évolution et le contexte historique du SSL en robotique ; un examen approfondi et une classification des techniques SSL et des méthodologies de suivi populaires ; différentes facettes du SSL ainsi que son état de l'art ; les méthodologies d'évaluation utilisées pour le SSL ; et un ensemble de défis et de motivations de recherche.

La localización de fuentes de sonido (SSL) en una plataforma robótica ha sido esencial en el esquema general de la audición de robots. Permite que un robot localice una fuente de sonido solo por sonido. Tiene un impacto importante en otros módulos de audición de robots, como la separación de fuentes, y enriquece la interacción humano-robot al complementar las capacidades perceptivas del robot. El objetivo principal de esta revisión es mapear a fondo el estado actual del campo SSL para el lector y proporcionar un punto de partida para SSL en robótica. En este sentido, presentamos: la evolución y el contexto histórico de SSL en robótica; una extensa revisión y clasificación de las técnicas SSL y las metodologías de seguimiento populares; diferentes facetas de SSL, así como su estado de la técnica; metodologías de evaluación utilizadas para SSL; y un conjunto de desafíos y motivaciones de investigación.

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.

كان توطين مصدر الصوت (SSL) في منصة روبوتية ضروريًا في المخطط العام لاختبار الروبوت. يسمح للروبوت بتحديد موقع مصدر الصوت عن طريق الصوت وحده. له تأثير مهم على وحدات اختبار الروبوت الأخرى، مثل فصل المصدر، ويثري التفاعل بين الإنسان والروبوت من خلال استكمال القدرات الإدراكية للروبوت. الهدف الرئيسي من هذه المراجعة هو رسم خريطة شاملة للحالة الراهنة لحقل طبقة المقابس الآمنة للقارئ وتوفير نقطة انطلاق إلى طبقة المقابس الآمنة في مجال الروبوتات. ولهذا الغرض، نقدم: تطور طبقة المقابس الآمنة وسياقها التاريخي في مجال الروبوتات ؛ ومراجعة وتصنيف شاملين لتقنيات طبقة المقابس الآمنة ومنهجيات التتبع الشائعة ؛ وجوانب مختلفة من طبقة المقابس الآمنة بالإضافة إلى أحدث ما توصلت إليه ؛ ومنهجيات التقييم المستخدمة في طبقة المقابس الآمنة ؛ ومجموعة من التحديات ودوافع البحث.

Keywords

Artificial intelligence, Acoustic source localization, Robot, Biomedical Engineering, Audio Signal Classification and Analysis, Source Separation, Set (abstract data type), FOS: Medical engineering, Human–robot interaction, Engineering, Environmental Sound Recognition, Context (archaeology), Field (mathematics), FOS: Mathematics, Speech Enhancement Techniques, Audio-Visual Speech Recognition, Biology, Acoustic Metamaterials and Phononic Crystals, Sound (geography), Human–computer interaction, Pure mathematics, Paleontology, Geomorphology, Geology, Robotics, FOS: Earth and related environmental sciences, Computer science, Programming language, Signal Processing, Computer Science, Physical Sciences, Computer vision, Mathematics

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    popularity
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    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
227
Top 1%
Top 1%
Top 1%
hybrid