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

Institutions

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

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of the X-Sketch: A Modular Skeleton Proprioception System for a Laparo-Endoscopic Single-Site Surgical Robot

Dehao Wei, Cheng‐Jin Du, Weidong Wang, Yulong Men et al.
IEEE Sensors Journal
Surgical Simulation and Training
article

Development of the X-Sketch: A Modular Skeleton Proprioception System for a Laparo-Endoscopic Single-Site Surgical Robot

Dehao Wei, Cheng‐Jin Du, Weidong Wang, Yulong Men, Zexin Cao
article en

Abstract

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.

IEEE Sensors JournalVol. 24(23)
Harbin Institute of Technology (CN), Italian Institute of Technology (IT), Tsinghua–Berkeley Shenzhen Institute (CN), Center for Micro-BioRobotics (IT)
National Natural Science Foundation of China
Zero hunger
Openalex Percentile: Top 66%
Surgical Simulation and Training
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.