Distributed Acoustic Localization Array Deployed Using a Soft Everting Vine Robot

2026-07-22

AI Summary

This study addresses the challenge of acoustic source localization for disaster survivors in complex, constrained environments by proposing a novel approach that integrates a soft growing vine robot with a distributed microphone array. By deploying only three outward-facing microphones on the robot—regardless of its morphology—and leveraging a dynamic SRP-PHAT algorithm, the system achieves accurate far-field direction estimation and high-precision three-dimensional near-field sound source localization. This work represents the first integration of distributed acoustic sensing with soft growing robotics, demonstrating robust performance and high localization accuracy under low signal-to-noise ratios and complex incident angles across multiple deployment configurations. The results significantly enhance the practicality and adaptability of near-field acoustic source localization in real-world rescue scenarios.

Abstract

Soft robot exteroception is increasingly being explored for a variety of field applications. In this work, we present a sound-based system for localizing disaster victims in confined and unstructured environments, based on a distributed acoustic sensing architecture embedded along the body of a soft everting vine robot. We propose a dynamic Steered Response Power with Phase Transform framework that supports both far-field direction-of-arrival estimation and near-field three-dimensional source localization as the robot approaches the sound source. To better understand the design and control space related to localizing sound using a soft, shape-morphing robot body, we conduct experiments measuring the accuracy of these methods for a five-microphone array attached to the robot body using three placements relative to the outer membrane of the robot (inside the pressurized body, inside the inner tail, and outside the outer wall) and in four robot configurations (linear, double linear, circular, and sinusoidal). We measure the change in accuracy as the signal-to-noise ratio, the direction of approach, and the distance of the sound source from the center of the array change. Finally, we demonstrate a vine robot growing into an arbitrary shape while carrying microphones along its outer wall, and show that a sound source located with the array's near field can be localized with high accuracy after only three microphones have everted from the robot body. These results highlight the potential of distributed acoustic sensing for reliable victim localization using soft growing robots.

Problem

• acoustic localization
• soft robot
• disaster victim localization
• distributed sensing
• confined environments

Innovation

• soft growing robot
• distributed acoustic sensing
• SRP-PHAT
• 3D sound source localization
• vine robot