Discovery of sound sources by an autonomous mobile robot.
Saved in:
| Title: | Discovery of sound sources by an autonomous mobile robot. |
|---|---|
| Authors: | Eric Martinson1, Alan Schultz1 |
| Source: | Autonomous Robots. Oct2009, Vol. 27 Issue 3, p221-237. 17p. |
| Subjects: | Autonomous robots, Mobile robots, Auditory scene analysis, Algorithms, Vector analysis, Classification |
| Abstract: | Abstract In this work, we describe an autonomous mobile robotic system for finding, investigating, and modeling ambient noise sources in the environment. The system has been fully implemented in two different environments, using two different robotic platforms and a variety of sound source types. Making use of a two-step approach to autonomous exploration of the auditory scene, the robot first quickly moves through the environment to find and roughly localize unknown sound sources using the auditory evidence grid algorithm. Then, using the knowledge gained from the initial exploration, the robot investigates each source in more depth, improving upon the initial localization accuracy, identifying volume and directivity, and, finally, building a classification vector useful for detecting the sound source in the future. [ABSTRACT FROM AUTHOR] |
| Copyright of Autonomous Robots is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 44815127 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Discovery of sound sources by an autonomous mobile robot. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Eric+Martinson%22">Eric Martinson</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Alan+Schultz%22">Alan Schultz</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Autonomous+Robots%22">Autonomous Robots</searchLink>. Oct2009, Vol. 27 Issue 3, p221-237. 17p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Autonomous+robots%22">Autonomous robots</searchLink><br /><searchLink fieldCode="DE" term="%22Mobile+robots%22">Mobile robots</searchLink><br /><searchLink fieldCode="DE" term="%22Auditory+scene+analysis%22">Auditory scene analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Vector+analysis%22">Vector analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Classification%22">Classification</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Abstract  In this work, we describe an autonomous mobile robotic system for finding, investigating, and modeling ambient noise sources in the environment. The system has been fully implemented in two different environments, using two different robotic platforms and a variety of sound source types. Making use of a two-step approach to autonomous exploration of the auditory scene, the robot first quickly moves through the environment to find and roughly localize unknown sound sources using the auditory evidence grid algorithm. Then, using the knowledge gained from the initial exploration, the robot investigates each source in more depth, improving upon the initial localization accuracy, identifying volume and directivity, and, finally, building a classification vector useful for detecting the sound source in the future. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Autonomous Robots is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=44815127 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10514-009-9123-1 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 221 Subjects: – SubjectFull: Autonomous robots Type: general – SubjectFull: Mobile robots Type: general – SubjectFull: Auditory scene analysis Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Vector analysis Type: general – SubjectFull: Classification Type: general Titles: – TitleFull: Discovery of sound sources by an autonomous mobile robot. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Eric Martinson – PersonEntity: Name: NameFull: Alan Schultz IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2009 Type: published Y: 2009 Identifiers: – Type: issn-print Value: 09295593 Numbering: – Type: volume Value: 27 – Type: issue Value: 3 Titles: – TitleFull: Autonomous Robots Type: main |
| ResultId | 1 |
