Ultrasound imaging is widely valued for its safety, non-invasiveness, and real-time capabilities but is often limited by operator variability, affecting image quality and reproducibility. Robot-assisted ultrasound may provide a solution by delivering more consistent, precise, and faster scans, potentially reducing human error and healthcare costs. Effective force control is crucial in robotic ultrasound scanning to ensure consistent image quality and patient safety. However, existing robotic ultrasound systems rely heavily on expensive commercial force sensors or the integrated sensors of commercial robotic arms, limiting their accessibility. To address these challenges, we developed a cost-effective, lightweight, 3D-printed force sensor and a hybrid position–force control strategy tailored for robotic ultrasound scanning. The system integrates patient-to-robot registration, automated scanning path planning, and multi-sensor data fusion, allowing the robot to autonomously locate the patient, target the region of interest, and maintain optimal contact force during scanning. Validation was conducted using an ultrasound-compatible abdominal aortic aneurysm (AAA) phantom created from patient CT data and healthy volunteer testing. For the volunteer testing, during a 1-min scan, 65% of the forces were within the good image range. Both volunteers reported no discomfort or pain during the whole procedure. These results demonstrate the potential of the system to provide safe, precise, and autonomous robotic ultrasound imaging in real-world conditions.

Accurate clip positioning (including position, direction, and orientation) in transcatheter mitral edge-to-edge repair (M-TEER) is challenging due to the complexity of manipulating tendon-driven concentric catheters under imaging guidance. Existing methods are limited to either task-space position/shape control or image-space joint control. This study presents a compact eight-DoF robot for controlling the PASCAL device, achieving closed-loop pose control in image space. Building on a prior variable curvature model, we develop a kinematic model that accounts for coupling between catheter handles and compensates for tip length variation. A prior sheath shape model is also integrated to support safer navigation in confined anatomy during clip adjustment. To achieve precise image-space pose control, we design a novel framework featuring a mapping strategy for independent control of clip position, direction, and orientation relative to registered imaging views, along with a Jacobian-based PID controller. Simulation results demonstrate effective independent control, with only direction adjustments exhibiting minor coupling with orientation (maximum deviation: 2.69$^{\circ }$). Experiments show that closed-loop control effectively mitigates catheter misalignment and rubber deformation, achieving average positional and angular RMSEs to 0.52 mm and 0.61$^{\circ }$. This robot provides precise, image-space pose control, which is expected to assist with the challenge of accurate clip positioning in M-TEER.

Ultrasound is safe, portable, and relatively low cost, and robotic ultrasound research is expanding across many diagnostic applications. Within this context, abdominal aortic aneurysm (AAA) screening remains comparatively unexplored, with few systems reporting end-to-end autonomous scanning and clinician-validated evaluation in volunteers. We present a conditionally autonomous (Level-3) robotic ultrasound system in which the operator defines the region of interest and confirms the target force band, after which the robot performs surface-constrained abdominal sweeps under force control and automatically selects diagnostic frames and estimates aortic diameter without further manual interaction during scanning. The system combines RGB-depth-based patient-to-robot registration, hybrid position–force control with a low-cost force sensor, and a post-acquisition image-analysis pipeline comprising rule-based aorta localisation, a composite image quality assessment (IQA) metric, and a transfer-learned U-Net segmentation baseline. In a feasibility study on ten healthy volunteers spanning BMI 18.6–33 and diverse sex and skin-tone profiles, the robot maintained stable contact within the target force band in all sessions and produced aortic images rated diagnostically acceptable by clinicians in all participants. Automated diameter measurements showed a mean absolute difference of 1.45 mm relative to clinician reference values, with 9/10 cases within 3 mm and all within the 5 mm screening criterion. Volunteer questionnaires indicated high levels of comfort and trust in the system. These results demonstrate the feasibility of operator-supervised, force-aware robotic AAA scanning and highlight the potential of low-cost robotic ultrasound for wider automated vascular imaging.

Structural heart interventions require precise navigation through tortuous and dynamic cardiac anatomies. However, current guide sheaths often lack sufficient maneuverability for positioning additional catheters. To address these limitations, this paper presents the design and evaluation of a robotic guide sheath with a dual-bendable, compressible tip. The sheath is capable of navigating complex cardiac anatomies for multiple valve interventions. The system consists of a soft continuum sheath tip driven by tendons, a laser-cut compact motorized actuation bed, and a joystick-controlled tendon actuation mechanism. A constant-curvature kinematic model maps actuation inputs to tip bending in 3D, while a custom software interface enables real-time control. Mechanical evaluation (tension, maximum bending, and contraction tests) demonstrated low actuation tension requirements (0.78 N), a wide bending range (from 80° to 90°), and promising tip compressibility (average 5 mm). Trajectory-following tests showed good accuracy, with an average error of 3.34 mm. Catheter guidance trials further validated the sheath’s ability to navigate to the right atrium and guide additional catheters effectively. This work presents a proof-of-concept robotic guide sheath with enhanced maneuverability and adaptability, establishing a foundation for future integration of sensing, automation, and clinical applications.