发表机构
University of Notre Dame; Pontifical Catholic University of Chile; Lincoln Laboratory, Massachusetts Institute of Technology（圣母大学; 智利天主教大学; 麻省理工学院林肯实验室）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究在受限非结构化环境中用软外翻藤蔓机器人定位灾难受害者，提出动态转向响应功率与相位变换框架，通过实验测量不同放置和配置下的定位准确性，展示藤蔓机器人生长定位声源能力，凸显分布式声学传感潜力。
AI 中文摘要
软机器人外部感知在各种现场应用中得到越来越多的探索。在这项工作中，我们提出了一种基于声音的系统，用于在受限和非结构化环境中定位灾难受害者，该系统基于沿软外翻藤蔓机器人身体嵌入的分布式声学传感架构。我们提出了一种动态转向响应功率与相位变换框架，该框架支持远场到达方向估计和机器人接近声源时的近场三维源定位。为了更好地理解与使用柔软、可变形机器人身体定位声音相关的设计和控制空间，我们进行了实验，测量了附着在机器人身体上的五麦克风阵列在相对于机器人外膜的三种放置方式（加压体内、内尾内和外壁外）以及四种机器人配置（线性、双线性、圆形和正弦形）下这些方法的准确性。我们测量了随着信噪比、接近方向和声源与阵列中心的距离变化时准确性的变化。最后，我们展示了一个藤蔓机器人在其外壁携带麦克风时生长成任意形状，并表明在只有三个麦克风从机器人身体外翻后，位于阵列近场的声源可以高精度定位。这些结果突出了分布式声学传感在使用软生长机器人进行可靠受害者定位方面的潜力。
英文摘要
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.
CommentsSebastian Lorca Godoy, Ciera McFarland, Michael Val, Antonio Alvarez Valdivia, Nathaniel Hanson, and Margaret McGuinness, "Distributed Acoustic Localization Array Deployed Using a Soft Everting Vine Robot", in IEEE International Conference on Intelligent Robots and Systems, 2026
