Bioinspired Amphibious Soft Robotics with Conformable Ultrasonic Array for Adaptive Defect Mapping and Terrain Reconstruction

  • Zhongming Chen
  • , Xiaopeng Wang
  • , Jiaqiang Xu
  • , Haotian Li
  • , Hongwu Su
  • , Qilin Hua*
  • , Guozhen Shen*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Inspection of confined, unstructured, and submerged environments (e.g., pipelines, ship hulls, and flooded infrastructure) remains a persistent challenge due to the limited adaptability of conventional rigid robots and sensing systems. Here, a bioinspired amphibious ultrasonic soft robot (AUS-R) is presented that integrates distributed conformable ultrasonic arrays with a fully soft, gas-driven locomotion system to achieve adaptive defect mapping and 3D terrain reconstruction in both terrestrial and aquatic settings. The AUS-R features a central array for forward-looking defect imaging and terrain echolocation, and peripheral tentacle arrays for boundary sensing and lateral defect detection, enabling real-time full-space environmental perception. Its waterproof and miniaturized design supports seamless navigation through narrow spaces and ensures functional integrity across air-water interfaces. Experimental demonstrations on object-level defects and submerged terrains validate the systems multifunctionality and robustness. This work establishes AUS-R as a versatile platform for non-destructive testing, infrastructure inspection, and autonomous environmental monitoring, laying the groundwork for intelligent, all-scenario robotic sensing systems.

Original languageEnglish
JournalAdvanced Functional Materials
DOIs
Publication statusAccepted/In press - 2025
Externally publishedYes

Keywords

  • embodied intelligence
  • flexible electronics
  • non-destructive testing
  • soft robotics
  • ultrasonic imaging

Fingerprint

Dive into the research topics of 'Bioinspired Amphibious Soft Robotics with Conformable Ultrasonic Array for Adaptive Defect Mapping and Terrain Reconstruction'. Together they form a unique fingerprint.

Cite this