A Single-Fiber Optical Frequency Domain Reflectometry (OFDR)-Based Shape Sensing of Concentric Tube Steerable Drilling Robots
Authors: Yash Kulkarni, Mobina Tavangarifard, Daniyal Maroufi, Mohsen Khadem, Justin E. Bird, Jeffrey H. Siewerdsen, Farshid Alambeigi
Organizations: Walker Department of Mechanical Engineering and Texas Robotics at The University of Texas at Austin, Austin, TX, 78712, USA. · M. Khadem is with the School of Informatics, University of Edinburgh, UK. · J. E. Bird is with the Department of Orthopedic Oncology, Division of Surgery, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA · J. H. Siewerdsen is with the Department of Imaging Physics, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
This paper introduces a novel shape-sensing approach for Concentric Tube Steerable Drilling Robots (CT-SDRs) based on Optical Frequency Domain Reflectometry (OFDR). Unlike traditional FBG-based methods, OFDR enables continuous strain measurement along the entire fiber length with enhanced spatial resolution. In the proposed method, a Shape Sensing Assembly (SSA) is first fabricated by integrating a single OFDR fiber with a flat NiTi wire. The calibrated SSA is then routed through and housed within the internal channel of a flexible drilling instrument, which is guided by the pre-shaped NiTi tube of the CT-SDR. In this configuration, the drilling instrument serves as a protective sheath for the SSA during drilling, eliminating the need for integration or adhesion to the instrument surface that is typical of conventional optical sensor approaches. The performance of the proposed SSA, integrated within the cannulated CT-SDR, was thoroughly evaluated under free-bending conditions and during drilling along multiple J-shaped trajectories in synthetic Sawbones phantoms. Results demonstrate accurate and reliable shape-sensing capability, confirming the feasibility and robustness of this integration strategy.
Figures & tables
Fig. 1: Conceptual illustration of the Sensorized CT-SDR compared to a conventional rigid drilling tool. Zoomed in view highlights the individual components of the CT-SDR. A cross-sectional view shows the proposed OFDR-based SSA passing through and housed within the internal channel of a flexible drilling instrument, which is guided by the pre-shaped NiTi tube of the CT-SDR.
Fig. 2: Rendered image of the Sensorized CT-SDR with labeled dimensions of its individual components. A zoomed-in view highlights the OFDR SSA and its dimensions in both top view and isometric view. The off-axis drill bit phenomenon is illustrated in the rendered image and further supported by an actual photograph of the drill bit, which also includes dimensional annotations.
Fig. 3: (A) Calibration jig with slots of varying radii of curvature. (B) Measured strain data collected in both positive and negative direction by OFDR SSA for various radii of curvature based on custom jig measurement.
Fig. 4: Calibration between strain and radius of curvature for the SSA in both positive and negative bending directions.
Fig. 5: Experimental Setup consisting of a KUKA Robot arm, Fluoroscopic X-Ray machine, Cannulated CT-SDR, and the OFDR shape sensor and interrogator. Close up views of the sensor inside the flexible drilling instrument is shown along with a zoomed in view of the flexible drilling instrument with dimensions and the NiTi tubes.
Fig. 6: (A) Strain along the length of the OFDR SSA during the Free Bending experiments for three radii of curvature. Shaded regions indicating the rigid section and the flexible section of the flexible drilling instrument. Standard deviations are also shown around the strain curves. (B) Reconstructed shape from measured strain across straight and curved section.
Fig. 7: (A) Fluoroscopic images taken during the drilling procedure showing the CT-SDR with OFDR sensor drilling different radii of curvatures. The drilled trajectory is shown in blue dashed lines for the linear trajectories and in orange dashed lines for the curved trajectory. The Sawbones border is marked in black dashed lines. (B) Strain along the length of the OFDR SSA during the drilling experiments and (C) shape reconstruction comparing measured and expected drilled trajectories from drilling experiments.
Radius of Curvature (mm)
Average Tip Error (mm)
Average Shape Error (mm)
w/o Sawbones
R117
0.97 [2.14 %]
0.59 [1.31 %]
R50
0.78 [1.73 %]
0.67 [1.49 %]
R39
1.32 [2.92 %]
0.41 [0.92 %]
w/ Sawbones
R∞
0.20 [0.44 %]
0.07 [0.16 %]
TABLE I: Tip and shape errors for free-space bending and drilling experiments
Continuum manipulators (CMs) are widely used in minimally invasive procedures due to their compliant structure and ability to navigate deep and confined anatomical environments. However, their distributed deformation makes force sensing, contact detection, localization, and force estimation challenging, particularly when interactions occur at unknown arc-length locations along the robot. To address this problem, we propose a cascade learning-based framework (CLF) for CMs instrumented with a single distributed Optical Frequency Domain Reflectometry (OFDR) fiber embedded along one side of the robot. The OFDR sensor provides dense strain measurements along the manipulator backbone, capturing strain perturbations caused by external interactions. The proposed CLF first detects contact using a Gradient Boosting classifier and then estimates contact location and interaction force magnitude using a CNN--FiLM model that predicts a spatial force distribution along the manipulator. Experimental validation on a sensorized tendon-driven CM in an obstructed environment demonstrates that a single distributed OFDR fiber provides sufficient information to jointly infer contact occurrence, location, and force in continuum manipulators.
Mobina Tavangarifard, Jonathan S. Kacines, Qiyu Li +1
Walker Department of Mechanical Engineering and Texas Robotics, The University of Texas at Austin, Austin, TX 78712, USA. · Department of Computer Science, The University of Texas at Austin, Austin, TX 78712, USA.
Continuum robots offer a promising approach for minimally invasive and natural-orifice surgical procedures due to their inherent compliance and dexterity. However, this flexibility also makes estimating the current shape of the robot challenging. Several approaches have been used to reconstruct the shape of these robots, including imaging, optical sensing, magnetic sensing, and resistive sensing. Strain sensors fabricated using direct laser writing (DLW) could provide an alternative sensing method. This technique involves using a laser to induce carbonization of certain polymers to create graphene patterns, such as strain sensors. In this paper, we demonstrate how a flexible continuum joint and a DLW sensor can be machined as one monolithic structure using the same laser and the same setup. The fabricated sensors are characterized using linear and nonlinear models, which are used to predict the joint angle with error as low as 1.76 degrees. Furthermore, we demonstrate how a DLW sensor can be used to implement closed-loop control in a robotic joint, achieving tracking error under 3 degrees.
Amber K. Rothe, Nidhi Malhotra, Jaydev P. Desai
Medical Robotics and Automation (RoboMed) Laboratory, Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332 USA
Shape and force sensing have long been critical bottlenecks in the development of compact capstan-driven continuum surgical robots, primarily due to the difficulty of obtaining cable tension information within the confined capstan assembly. To overcome these challenges, this paper presents an integrated design-modeling-sensing approach based on the concept of actuation-perception co-design. A compliant element is introduced into the motor mounting bracket of the drive system, enabling micro-deformation under the cable reaction force and thereby allowing real-time cable tension measurement without occupying the compact capstan space. To address the modeling complexity arising from unconventional joint configurations introduced by the spatial cable routing strategy, a parallel computation framework based on a multibody short-thick-beam model is proposed, which captures shear effects in short beam segments and synergistic multi-cable interactions while achieving real-time performance. Building on this framework, stable shape and force sensing is achieved by incorporating a proximal multi-axis force/torque sensor as an additional measurement anchor. Following this design-modeling-sensing framework, capstan-driven continuum surgical robots with single- and dual-segment configurations are developed. Experimental results validate the proposed framework in both single- and dual-segment continuum robots, demonstrating real-time tip pose estimation together with contact force and location perception. By enabling cable tension feedback without compromising the compact capstan architecture, the proposed framework makes integrated perception feasible for capstan-driven continuum surgical robots.
Gang Zhang, Yufu Qiu, Junyan Yan +3
Department of Mechanical and Automation Engineering and T Stone Robotics Institute, The Chinese University of Hong Kong, Hong Kong · School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China · state Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology (HUST), Wuhan, China +1