Optimal Teleoperation Control for Flexible Endoscopic Robots Based on Neurodynamic Optimization
Author:
Affiliation:

Clc Number:

T

Fund Project:

Science and Technology Program of Fujian (2024I0005), and Health Major Scientific Research Program of Fujian (2021ZD01003)

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Flexible endoscopic robots, with their continuum structural characteristics, demonstrate unique advantages in minimally invasive surgery. However, the inherent nonlinear deformation features of continuum structures pose significant challenges to motion control precision. To address this technical bottleneck, this paper proposes an optimal teleoperation control method for flexible endoscopic robots based on neurodynamic optimization. First, a master-slave motion mapping mechanism in image space is established, coupled with a kinematic model of the flexible endoscope, to achieve accurate mapping between image feature velocities and driving velocities. Second, joint motion constraints are incorporated to formulate the robot control as a quadratic programming based optimal control problem, which is efficiently solved using a neurodynamic-based real-time solver. Experimental validation is conducted on a ureteroscopic robotic platform. Results demonstrate that the proposed method effectively suppresses manual operation errors and velocity oscillations, maintaining target tracking errors within 2.5% while significantly enhancing the accuracy and stability of instrument manipulation during lithotripsy procedures.

    Reference
    Related
    Cited by
Get Citation

ZHANG Jieyang, HE Shuai, DENG Zhen, et al. Optimal Teleoperation Control for Flexible Endoscopic Robots Based on Neurodynamic Optimization[J]. Journal of Integration Technology,2025,14(2):3-12

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:September 26,2024
  • Revised:December 08,2024
  • Adopted:December 10,2024
  • Online: January 03,2025
  • Published:
Article QR Code