Detecting acoustic reflectors using a robot's ego-noise

TL;DR

This paper introduces a nonintrusive audio-based method for robots to detect nearby acoustic reflectors like walls using ego-noise, enabling collision avoidance without traditional sensors.

Contribution

The paper presents a novel probabilistic approach to estimate reflector proximity using ego-noise, outperforming previous intrusive methods especially in loud noise conditions.

Findings

Accurately estimates reflector distance up to 1 meter

Outperforms previous intrusive approaches in loud ego-noise

Enables collision avoidance using only audio sensors

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 nonintrusive 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.