Selectively Actuated Fiberbots for High-precision Minimally Invasive Surgery
Authors: Jinshi Zhao, Libaihe Tian, Alex Ranne, Qindong Zheng, Yue Li, Xiaotong Guo, Ziqi Yang, Ali Anil Demircali, +4 more
Organizations: Department of Metabolism, Digestion and Reproduction, Imperial College London, SW7 2AZ, UK · Hamlyn Centre for Robotic Surgery, Imperial College London, SW7 2AZ, UK · Department of Bioengineering, Imperial College London, SW7 2AZ, UK · Department of Biomedical Engineering, University of Glasgow, G12 8QQ, UK
Long, slender instruments are essential for minimally invasive surgery (MIS), but achieving precise distal manipulation becomes increasingly difficult when actuation extends along the entire instrument. Here, we present an electrothermally actuated fiber-based robot designed for MIS procedures, in which Joule heating is concentrated in the distal active segment. The fiber is fabricated using a thermal drawing process and uses embedded metallic wires for thermal actuation. This robotic fiber, 1.9 mm in diameter and 1.2 m in length, can precisely manipulate surgical laser fibers with positional precision below 100 μm. The compact size of the fiber robot allows it to pass through the working channel of a flexible endoscope, while keeping both devices mechanically uncoupled to allow independent motion. A phantom demonstration combining the robotic fiber with a da Vinci instrument conceptually demonstrated its compatibility with existing endoscopic systems for clinical applications. Our robotic fiber enables precise distal motion and holds the potential to improve clinical outcomes by enhancing precision in MIS procedures.
Figures & tables
Fig. 1: Schematic diagram of the selectively actuated fiberbot.
Fig. 2: Fiber fabrication. (a) Schematic diagram of the thermal drawing process, showing wire spools feeding wires during drawing. (b) Cross-sectional design of the fiber. (c) Microscopic image of the fiber cross-section with exposed wires.
Fig. 3: Selectively actuated Fiberbot with handle.
Fig. 4: Fiberbot motion characterization. (a) Fiberbot actuation and characterization setup. (b) Fiberbot tip positions resulting from 500 random input voltage sets. Each color represents one of the three possible combinations of two simultaneously actuated wire sets. (c,d) Relationship between applied voltages (c), powers (d) and the vector magnitude of the fiber tip position along their corresponding actuation directions. (e,f) Measured (blue) versus desired (orange) spiral and star shape paths.
Fig. 5: Temperature characterization. (a) A series of thermal imaging camera images showing the temperature distribution of the fiber at various applied voltages. (b) Maximum (orange) and minimum (blue) temperatures at various applied voltages measured using a thermal camera. (c) Fiber tip displacement (blue) and temperature difference (orange) between maximum and minimum temperatures under various applied voltages. (d,e) Thermal camera setup and corresponding image showing a side view of the selectively actuated fiber.
Fig. 6: Comparison of the required actuation power between the selectively actuated fiberbot developed in this work and the fiberbot reported in the previous work [ 4 ] . (a) Schematic of the working principle of the selectively actuated fiberbot developed in this work. (b) Schematic of the actuation approach used in the previous work. (c) Calculated total actuation power required to achieve a 2 mm tip displacement for different passive-section lengths.
Fig. 7: The da Vinci® surgical instrument integration and endoluminal phantom demonstration. (a) The integration between the da Vinci® surgical robot and the fiber actuator. (b) Experimental setup of the abdominal phantom study. (c) Retraction of the phantom surface layer using a grasper to expose the simulated tumor. (d) Fiberbot tip scanning along the simulated tumor boundary, with an optical fiber inserted through its central lumen. (e) Fiberbot tip motion path around the simulated tumor, indicated by the red trace.
Surgical robots require highly dexterous and compact robotic systems capable of operating effectively within confined anatomical spaces. However, due to limited access provided by a single incision, the miniaturization and maneuverability of these robots still need to be improved. In this paper, we propose the design and modeling of a single-port three-arm robotic tool containing one major cannula (7.14 mm outer diameter (OD)) and three steerable minor cannulas (1.93 mm OD). By integrating the proposed 12 degrees-of-freedom (DoFs) steerable robotic tool with a 7-DoF robotic arm, this robotic system can potentially achieve multi-arm manipulation capability. We present the design of the steerable robotic tool consisting of tendon-driven joints controlled by a compact actuation system, derive the kinematic model, and validate both the static and kinematic models through experiments. The performance is evaluated with the root mean square error (RMSE) and mean absolute error (MAE) computed between the experimental data and the kinematic model.
Nazia H. Dana, Harith S. Gallage, Ismail A. Auta +2
Robotics and Healthcare Systems (RoboHS) Laboratory, Department of Mechanical Engineering, University of Nevada, Las Vegas (UNLV), Las Vegas, NV, USA
Robot-Assisted Minimally Invasive Surgery (RAMIS) enhances surgeon dexterity, with newer platforms leveraging haptic feedback to further improve performance. Such force information has broader potential to inform performance assessment, tactile localization, and surgical autonomy. This motivates the need for accessible approaches to integrating force sensing into RAMIS tools. This work presents a method for integrating a six-axis commercial force sensor into the distal end of a standard cable-driven surgical instrument, enabling end-effector force measurement while preserving the original mechanical functionality of the device. The proposed design emphasizes reproducibility and accessibility for research applications, requiring no specialized manufacturing tools. A transformer neural network integrates force sensor measurements with robot state information to aid estimation of applied forces at the end-effector, compensating for internal cable forces arising from actuation. Our proposed approach achieved normalized errors below 6%, and generalized to unseen conditions better than purely proximal data-driven sensing approaches. High internal cable forces caused sensor saturation and reduced axial force observability, which can degrade performance along the tool's major axis and under higher load conditions. Given current levels of performance, the balance of system integrability and performance enables applications and research into timely topics of haptic feedback, skill assessment, and force-informed autonomy in RAMIS. Videos and code are available at https://enhanced-telerobotics.github.io/shaft_force_sensing/.
Shuyuan Yang, Grant Boone, Timo Markert +4
Department of Electrical, Computer, and Systems Engineering, Case Western Reserve University, Cleveland, OH 44016, USA · Department of Mechanical and Aerospace Engineering, Case Western Reserve University, Cleveland, OH 44106, USA · Resense GmbH, Germany +3
Existing stretch and touch sensors for robots are generally expensive with respect to at least one of material costs, required manufacturing equipment, or manufacturing time. We present and experimentally characterize a conductive fiber made using only inexpensive commercial off-the-shelf parts (conductive thread at 0.07/ft,siliconetubingat0.94/ft) and tools (loop-style needle threader at $2), which can be manufactured quickly (20 cm length in 2 minutes.) We demonstrate its use as a resistive strain sensor with three applications: Triggering a grasp in a pneumatically actuated assistive finger, sensing the pose of a pneumatically actuated robotic strap, and estimating the pose of a flexible solid. We also demonstrate that it can be used as a capacitive sensor with two applications: First, as a touch sensor which triggers a commercial robot arm to move, and second, as a near-field sensor enabling the robot arm to follow a moving hand. The capacitive sensors are knitted, showcasing the high flexibility of the fiber. We discuss methods for improving manufacturing scalability and their cost trade-offs. Finally, we demonstrate a method for repairing a cut fiber.
Christian Diaz Herrera, Srushti Raste, Simin Liu +10
Patton · Wesleyan University · Computer Science, Department of Mathematics and Computer Science +1