Human-mimetic binaural ear design and sound source direction estimation for task realization of musculoskeletal humanoids

TL;DR

This paper presents a human-like auditory system for musculoskeletal humanoids, enabling environment recognition and sound source localization in complex, noisy settings, by mimicking human ear structure and neural processing.

Contribution

It introduces a novel human-mimetic binaural ear and sound processing system integrated into a humanoid, advancing auditory perception capabilities for task execution.

Findings

Successful sound source direction estimation in noisy environments

Effective environmental sound detection mimicking human central nervous processing

Enhanced task performance using auditory cues in complex settings

Abstract

Human-like environment recognition by musculoskeletal humanoids is important for task realization in real complex environments and for use as dummies for test subjects. Humans integrate various sensory information to perceive their surroundings, and hearing is particularly useful for recognizing objects out of view or out of touch. In this research, we aim to realize human-like auditory environmental recognition and task realization for musculoskeletal humanoids by equipping them with a human-like auditory processing system. Humans realize sound-based environmental recognition by estimating directions of the sound sources and detecting environmental sounds based on changes in the time and frequency domain of incoming sounds and the integration of auditory information in the central nervous system. We propose a human mimetic auditory information processing system, which consists of three components: the human mimetic binaural ear unit, which mimics human ear structure and characteristics, the sound source direction estimation system, and the environmental sound detection system, which mimics processing in the central nervous system. We apply it to Musashi, a human mimetic musculoskeletal humanoid, and have it perform tasks that require sound information outside of view in real noisy environments to confirm the usefulness of the proposed methods.