低成本管道内中心对准与检测的最小传感机器人
Low-Cost Underwater In-Pipe Centering and Inspection Using a Minimal-Sensing Robot
AI总结：
本文提出了一种低成本水下管道内中心对准与检测方法，利用IMU、压力传感器和双声纳实现自主导航与检测，无需复杂多传感器系统。
摘要：
水下 submerged 管道的自主检测具有挑战性，由于受限的几何形状、浑浊度以及可靠的定位线索稀缺。本文提出了一种最小传感策略，使自由游动的水下机器人能够仅使用IMU、压力传感器和两个声纳（一个向下单束声纳和一个旋转360度声纳）来对准并穿越已知半径的水下管道。我们介绍了一种计算效率高的方法，用于从单束声纳强度数据中提取距离估计，从而在嘈杂和回声条件下实现可靠壁面检测。一个闭合形式的几何模型利用两个声纳距离来估计管道中心，而一个自适应的、基于置信度加权的比例-微分（PD）控制器在穿越过程中维持对准。该系统不需要多普勒速度计、外部跟踪或复杂的多传感器阵列。在使用Blue Robotics BlueROV2重型遥控潜水器进行的46厘米直径水下管道实验中，尽管存在环境流体和结构变形，仍实现了稳定的对准和成功的全管道穿越。这些结果表明，通过轻量、计算高效感测和处理架构可以实现可靠的管道内导航和检测，推动了在受限环境中自主水下检测的实用性。
英文摘要：
Autonomous underwater inspection of submerged pipelines is challenging due to confined geometries, turbidity, and the scarcity of reliable localization cues. This paper presents a minimal-sensing strategy that enables a free-swimming underwater robot to center itself and traverse a flooded pipe of known radius using only an IMU, a pressure sensor, and two sonars: a downward-facing single-beam sonar and a rotating 360 degree sonar. We introduce a computationally efficient method for extracting range estimates from single-beam sonar intensity data, enabling reliable wall detection in noisy and reverberant conditions. A closed-form geometric model leverages the two sonar ranges to estimate the pipe center, and an adaptive, confidence-weighted proportional-derivative (PD) controller maintains alignment during traversal. The system requires no Doppler velocity log, external tracking, or complex multi-sensor arrays. Experiments in a submerged 46 cm-diameter pipe using a Blue Robotics BlueROV2 heavy remotely operated vehicle demonstrate stable centering and successful full-pipe traversal despite ambient flow and structural deformations. These results show that reliable in-pipe navigation and inspection can be achieved with a lightweight, computationally efficient sensing and processing architecture, advancing the practicality of autonomous underwater inspection in confined environments.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
