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Soft robotics is advancing the use of flexible materials for adaptable robotic systems. Membrane-actuated soft robots address the limitations of traditional soft robots by using pressurized, extensible membranes to achieve stable, large deformations, yet control and state estimation remain challenging due to their complex deformation dynamics. This paper presents a novel modeling approach for liquid-driven ballooning membranes, employing an ellipsoid approximation to model shape and stretch under planar deformation. Relying solely on intrinsic feedback from pressure data and controlled liquid volume, this approach enables accurate membrane state estimation. We demonstrate the effectiveness of the proposed model for ballooning membrane-based actuators by experimental validation, obtaining the indentation depth error of $RMSE_{h_2}=0.80\;$mm, which is $23\%$ of the indentation range and $6.67\%$ of the unindented actuator height range. For the force estimation, the error range is obtained to be $RMSE_{F}=0.15\;$N which is $10\%$ of the measured force range.

In robotic-assisted partial nephrectomy, surgeons remove a part of a kidney often due to the presence of a mass. A drop-in ultrasound probe paired to a surgical robot is deployed to execute multiple swipes over the kidney surface to localise the mass and define the margins of resection. This sub-task is challenging and must be performed by a highly skilled surgeon. Automating this sub-task may reduce cognitive load for the surgeon and improve patient outcomes. The overall goal of this work is to autonomously move the ultrasound probe on the surface of the kidney taking advantage of the use of the Pneumatically Attachable Flexible (PAF) rail system, a soft robotic device used for organ scanning and repositioning. First, we integrate a shape-sensing optical fibre into the PAF rail system to evaluate the curvature of target organs in robotic-assisted laparoscopic surgery. Then, we investigate the impact of the stiffness of the material of the PAF rail on the curvature sensing accuracy, considering that soft targets are present in the surgical field. Finally, we use shape sensing to plan the trajectory of the da Vinci surgical robot paired with a drop-in ultrasound probe and autonomously generate an Ultrasound scan of a kidney phantom., Comment: 9 pages, 11 figures

Colonoscopy is considered the golden standard for cancer screening of the lower gastrointestinal (GI) tract, with screening programs all over the world considering lowering the recommended screening age. Nonetheless, conventional colonoscopy can cause discomfort to patients due to the forces occurring between colonoscopes and the walls of the colon. Robotic solutions have been proposed to reduce discomfort, and improve accessibility and image quality. Aiming at addressing the limitations of traditional and robotic colonoscopy, in this paper, we present the SoftSCREEN System, a novel Soft Shapeshifting Capsule Robot for Endoscopy based on Eversion Navigation. A plurality of tracks surrounds the body of the system. These tracks are driven by a single motor paired with a worm gear and evert from the internal rigid chassis, enabling fullbody track-based navigation. Two inflatable toroidal chambers enclosing this rigid chassis and passing through the tracks, cause them to displace when inflated. This displacement can be used to regulate the contact with the surrounding wall, thus enabling traction control and adjustment of the overall system diameter to match the local lumen size. The design of the first tethered prototype at 2:1 scale of the SoftSCREEN system is presented in this work. The experimental results show efficient navigation capabilities for different lumen diameters and curvatures, paving the way for a novel robot capable of robust navigation and reliable control of the imaging, with potential for applications beyond colonoscopy, including gastroscopy and capsule endoscopy., Comment: 9 pages, 8 figures

With soft robotics being increasingly employed in settings demanding high and controlled contact forces, recent research has demonstrated the use of soft robots to estimate or intrinsically sense forces without requiring external sensing mechanisms. Whilst this has mainly been shown in tendon-based continuum manipulators or deformable robots comprising of push-pull rod actuation, fluid drives still pose great challenges due to high actuation variability and nonlinear mechanical system responses. In this work we investigate the capabilities of a hydraulic, parallel soft robot to intrinsically sense and subsequently control contact forces. A comprehensive algorithm is derived for static, quasi-static and dynamic force sensing which relies on fluid volume and pressure information of the system. The algorithm is validated for a single degree-of-freedom soft fluidic actuator. Results indicate that axial forces acting on a single actuator can be estimated with an accuracy of 0.56 +- 0.66N within the validated range of 0 to 6N in a quasi-static configuration. The force sensing methodology is applied to force control in a single actuator as well as the coupled parallel robot. It can be seen that forces are accurately controllable for both systems, with the capability of controlling directional contact forces in case of the multi degree-of-freedom parallel soft robot.

Objective: In this work we address limitations in state-of-the-art ultrasound robots by designing and integrating a novel soft robotic system for ultrasound imaging. It employs the inherent qualities of soft fluidic actuators to establish safe, adaptable interaction between ultrasound probe and patient. Methods: We acquire clinical data to determine the movement ranges and force levels required in prenatal foetal ultrasound imaging and design the soft robotic end-effector accordingly. We verify its mechanical characteristics, derive and validate a kinetostatic model and demonstrate controllability and imaging capabilities on an ultrasound phantom. Results: The soft robot exhibits the desired stiffness characteristics and is able to reach 100% of the required workspace when no external force is present, and 95% of the workspace when considering its compliance. The model can accurately predict the end-effector pose with a mean error of 1.18+/-0.29mm in position and 0.92+/-0.47deg in orientation. The derived controller is, with an average position error of 0.39mm, able to track a target pose efficiently without and with externally applied loads. Ultrasound images acquired with the system are of equally good quality compared to a manual sonographer scan. Conclusion: The system is able to withstand loads commonly applied during foetal ultrasound scans and remains controllable with a motion range similar to manual scanning. Significance: The proposed soft robot presents a safe, cost-effective solution to offloading sonographers in day-to-day scanning routines. The design and modelling paradigms are greatly generalizable and particularly suitable for designing soft robots for physical interaction tasks.

The development of robotic-assisted extracorporeal ultrasound systems has a long history and a number of projects have been proposed since the 1990s focusing on different technical aspects. These aim to resolve the deficiencies of on-site manual manipulation of hand-held ultrasound probes. This paper presents the recent ongoing developments of a series of bespoke robotic systems, including both single-arm and dual-arm versions, for a project known as intelligent Fetal Imaging and Diagnosis (iFIND). After a brief review of the development history of the extracorporeal ultrasound robotic system used for fetal and abdominal examinations, the specific aim of the iFIND robots, the design evolution, the implementation details of each version, and the initial clinical feedback of the iFIND robot series are presented. Based on the preliminary testing of these newly-proposed robots on 42 volunteers, the successful and re-liable working of the mechatronic systems were validated. Analysis of a participant questionnaire indicates a comfortable scanning experience for the volunteers and a good acceptance rate to being scanned by the robots., Comment: 12 pages, 6 figures, TAROS conference 2019