Robust Sound Localization: An Application of an Auditory Perception System for a Humanoid Robot

Abstract

Localizing sounds with different frequency and time domain characteristics in a dynamic listening environment is a challenging task that has not been explored in the field of robotics as much as other perceptual tasks. This thesis presents an integrated auditory system for a humanoid robot, currently under development, that will, among other things, learn to localize normal, everyday sounds in a realistic environment. The hardware and software has been designed and developed to take full advantage of the features and capabilities of the humanoid robot of which it will be an integral component. Sounds with different frequency components and time domain characteristics have to be localized using different cues; a neural network is also presented that has been developed off-line to learn to integrate the various auditory cues, using primarily visual data to perform self-supervised training.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1995
Accession Number
ADA458133

Entities

People

  • Robert E. Irie

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acoustic Signals
  • Artificial Intelligence
  • Auditory Perception
  • Computational Science
  • Computer Languages
  • Computer Science
  • Computer Vision
  • Computers
  • Detectors
  • Electrical Engineering
  • Information Processing
  • Lisp Programming Language
  • Neural Networks
  • Parallel Computing
  • Parallel Processing
  • Perception
  • Signal Processing

Fields of Study

  • Computer science

Readers

  • Acoustical Oceanography.
  • Neural Network Machine Learning.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Neural Networks
  • Autonomy