自动化学报2026，Vol.52Issue(6)：1291-1303,13.DOI:10.16383/j.aas.c250530
基于集合贝叶斯交互基元的机械臂自主肝脏超声扫查
Autonomous Liver Ultrasound Scanning via Robotic Arm Using Ensemble Bayesian Interaction Primitives
摘要
Abstract
To advance liver ultrasound examination,this study proposes a fully autonomous robotic arm ultra-sound scanning method based on ensemble Bayesian interaction primitives(enBIP),and develops the correspond-ing experimental system.The proposed method consists of two sequential stages:Initial positioning and imitation learning.In the initial positioning stage,the system guides the probe to establish contact with the patient using RGB-D images and determines the transition to the imitation learning stage based on real-time ultrasound images.In the imitation learning stage,the system encodes expert scanning skills into ultrasound image state trajectories and probe motion trajectories,and learns to reproduce these skills using enBIP.Consequently,fully autonomous ro-botic arm liver ultrasound scanning is achieved.In addition,the proposed framework was experimentally validated on a human abdominal phantom.Experimental results demonstrate that the proposed method successfully per-forms the liver scanning task without human intervention,highlighting its potential for clinical application.关键词
机械臂/自主超声扫查/模仿学习/集合贝叶斯交互基元Key words
robotic arm/autonomous ultrasound scanning/imitation learning/ensemble Bayesian interaction primitives引用本文复制引用
马骥,赵悦,刘壮,胡悦,刘健行,沈毅..基于集合贝叶斯交互基元的机械臂自主肝脏超声扫查[J].自动化学报,2026,52(6):1291-1303,13.基金项目
国家自然科学基金(62473108,62173116,62371167,62373127),国家资助博士后研究人员计划(GZB20250957),中国博士后科学基金(2024M764189)资助 Supported by National Natural Science Foundation of China(62473108,62173116,62371167,62373127),Postdoctoral Fellow-ship Program of China Postdoctoral Science Foundation(GZB20250957),and China Postdoctoral Science Foundation(2024M764189) （62473108,62173116,62371167,62373127）
