Detecting Acoustic Reflectors using a Robot's Ego-noise

Usama Saqib, Antoine Deleforge, Jesper Rindom Jensen

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

1 Citation (Scopus)

Abstract

In this paper, we propose a method to estimate the proximity of an acoustic reflector, e.g., a wall, using ego-noise, i.e., the noise produced by the moving parts of a listening robot. This is achieved by estimating the times of arrival of acoustic echoes reflected from the surface. Simulated experiments show that the proposed non-intrusive approach is capable of accurately estimating the distance of a reflector up to 1 meter and outperforms a previously proposed intrusive approach under loud ego-noise conditions. The proposed method is helped by a probabilistic echo detector that estimates whether or not an acoustic reflector is within a short range of the robotic platform. This preliminary investigation paves the way towards a new kind of collision avoidance system that would purely rely on audio sensors rather than conventional proximity sensors.
Original languageEnglish
Title of host publicationInternational Conference on Acoustic, Speech and Signal Processing
Number of pages5
Volume2021-June
PublisherIEEE
Publication date2021
Pages466-470
Article number9414061
ISBN (Print)978-1-7281-7606-2
ISBN (Electronic)978-1-7281-7605-5
DOIs
Publication statusPublished - 2021
Event ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - Toronto, Canada
Duration: 6 Jun 202111 Jun 2021

Conference

Conference ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Country/TerritoryCanada
CityToronto
Period06/06/202111/06/2021
SeriesI E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings
ISSN1520-6149

Keywords

  • Echo detection
  • Ego-noise
  • Robot/Drone audition
  • Robotics

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