EchoSLAM: Simultaneous localization and mapping with acoustic echoes

Abstract

We address the problem of jointly localizing a robot in an unknown room and estimating the room geometry from echoes. Unlike earlier work using echoes, we assume a completely autonomous setup with (near) collocated microphone and the acoustic source. We first introduce a simple, easy to analyze estimator, and prove that the sequence of room and trajectory estimates converges to the true values. Next, we approach the problem from a Bayesian point of view, and propose a more general solution which does not require any assumptions on motion and measurement model of the robot. In addition to theoretical analysis, we validate both estimators numerically.

Audio-motor integration for robot audition

“…Both ILD and IPD are known to be subject-dependent and frequency-dependent cues. This is captured by the so-called head related transfer functions (HRTFs) determined by the shape Audio-motor integration [8,9,20,30,31,33,34,38,41,48,55,60,61] Active audition [4,6,39,40,45,67]…”

“…In [55,9,48] mobile robots are used to actively collect several viewpoints of one or several emitting sound sources in order to accurately estimate their azimuths and distances. More broadly, studies tackling the problem of audio-based simultaneous localization and mapping (SLAM) have recently emerged [19,34]. Interestingly, [34] does it with a single microphone at multiple viewpoints thanks to acoustic echoes.…”

“…More broadly, studies tackling the problem of audio-based simultaneous localization and mapping (SLAM) have recently emerged [19,34]. Interestingly, [34] does it with a single microphone at multiple viewpoints thanks to acoustic echoes. Note that the above mentioned studies rely on static localization techniques applied from different viewpoints.…”

Kinetic Euclidean Distance Matrices

“…Applications are emerging where sensing is opportunistic and the positions of reference objects are not known [19]; in Section VI-D, we present a simulated example of global positioning with unknown satellite trajectories. This problem is further related to simultaneous localization and mapping (SLAM) [20], [21]. Kinetic distance geometry problems are common in computer vision.…”

A New Method of Simultaneous Localization and Mapping for Mobile Robots Using Acoustic Landmarks

“…Sci. 2019, 9, 1352 2 of 24 the potential for wide application in areas including autonomous robots, hearing aids, smart cars, and virtual reality devices [12,13].…”