2025/10/09 by Zihan Li, Yi‐Wei Xu, Li, Zihan +17
Engineering · Physics and Astronomy · #FOS: Computer and information sciences #Micro and Nano Robotics #Robotics (cs.RO) #Robotics and Sensor-Based Localization #Soft Robotics and Applications
paper · pdf · doi:10.48550/arxiv.2510.08106
openalex publication_date 2025/10/09 · openalex created_date 2025/10/11 · openalex updated_date 2026/07/28
Liver disease is a major global health burden. While ultrasound is the first-line diagnostic tool, liver sonography requires locating multiple non-continuous planes from positions where target structures are often not visible, for biometric assessment and lesion detection, requiring significant expertise. However, expert sonographers are severely scarce in resource-limited regions. Here, we develop an autonomous lightweight ultrasound robot comprising an AI agent that integrates multi-modal perception with memory attention for localization of unseen target structures, and a 588-gram 6-degrees-of-freedom cable-driven robot. By mounting on the abdomen, the system enhances robustness against motion. Our robot can autonomously acquire expert-level standard liver ultrasound planes and detect pathology in patients, including two from Xining, a 2261-meter-altitude city with limited medical resources. Our system performs effectively on rapid-motion individuals and in wilderness environments. This work represents the first demonstration of autonomous sonography across multiple challenging scenarios, potentially transforming access to expert-level diagnostics in underserved regions.