Development of the X-Sketch: A Modular Skeleton Proprioception System for a Laparo-Endoscopic Single-Site Surgical Robot
The development of continuum robots with embedded sensing systems has been a research focus over the last decade. Specifically, for the robot-assisted laparo-endoscopic single-site surgical (R-LESS) system, an economical solution that allows the integration of an electromagnetic (EM)-compatible shape-proprioception system is needed. In this article, we propose a modular sensing system named X-Sketch for the R-LESS system. The system comprises four fiber Bragg grating (FBG) channels integrated with 3-D-printed elastic joints that enable the detection of curvature variations. The modularity and customizability are achieved by the stacking design of the flexible joints and sensing units. The skeleton of the arm is constructed by an analytical kinematics process of the curvature information, during which a neural network (NN) is employed to perform the curvature regression. For the experiment, an R-LESS arm prototype integrated with the X-Sketch system is developed. Calibration and experimental evaluation are then conducted to assess the performance of the proposed sensing system. The results demonstrate the performance of the proposed system, achieving an average tip position error of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2.23~\pm ~0.64$ </tex-math></inline-formula> mm, corresponding to <5% of the system’s length, suggesting the potential for X-Sketch application in R-LESS surgical operations.
Authors
- Dehao Wei (ORCID: https://orcid.org/0000-0001-7249-6410)
- Cheng‐Jin Du (ORCID: https://orcid.org/0000-0002-9879-9409)
- Weidong Wang (ORCID: https://orcid.org/0000-0002-1236-8350)
- Yulong Men (ORCID: https://orcid.org/0009-0002-8145-8859)
- Zexin Cao
Institutions
- Harbin Institute of Technology (CN)
- Italian Institute of Technology (IT)
- Tsinghua–Berkeley Shenzhen Institute (CN)
- Center for Micro-BioRobotics (IT)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2024-10-17
- DOI
- https://doi.org/10.1109/jsen.2024.3471776
- Primary Topic
- Surgical Simulation and Training
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China