Autonomous Robotic Ultrasound Scanning for Liver Interventions: an Integrated Redundancy Resolution and Motion Control Framework

Peng Chen, Hiroshi Yokoi, Bo Zhang — Tue, 10 Mar 2026 00:00:00 +0800

Ultrasound-guided interventions, such as liver tumor puncture and ablation, are critical procedures that depend fundamentally on the acquisition of stable, high-quality, real-time imaging. Manual ultrasound scanning, however, suffers from significant operator-dependency and motion instability, which can compromise diagnostic accuracy and procedural outcomes. To address these limitations, this paper introduces a novel, integrated motion control framework for a 7-axis redundant robotic arm designed to perform automated, high-fidelity sector scans. Ultrasound-guided interventions, such as liver tumor puncture and ablation, necessitate stable and high-quality real-time imaging for procedural success. However, manual scanning is often hindered by operator dependency and inherent motion instability. This paper presents a novel motion control framework for a 7-DOF redundant robotic arm, specifically optimized for automated, high-fidelity sector scans. The methodology integrates a human-in-the-loop compliant guidance mode with an autonomous optimization-based execution scheme. The workflow enables clinicians to manually position the probe via a free-drive mode, after which the system computes a kinematically optimal trajectory by considering clinical ergonomics and joint limit avoidance. A real-time, Jacobian-based redundancy resolution controller is implemented to translate task-space trajectories into smooth joint-level commands, incorporating a null-space optimization strategy with a Clinical Dexterity & Safety Index (CDSI) to ensure avoidance of singularities and joint limits. Experimental results demonstrate that the proposed system achieves sub-millimeter tracking accuracy with a mean position error of <0.3 mm and a multi-axis orientation error of <1 deg. Furthermore, compared to standard SDK-based methods, our framework significantly enhances motion smoothness, reducing end-effector jerk by 30% and maintaining a higher directional manipulability (w_scan) throughout the scanning phase. This framework successfully transitions from manual guidance to automated execution, ensuring highly repeatable and stable ultrasound imaging for critical interventional procedures.

Intelligent Systems & Robotic Mechanics

Autonomous Robotic Ultrasound Scanning for Liver Interventions: an Integrated Redundancy Resolution and Motion Control Framework