Output-Bounded and RBFNN-Based Position Tracking and Adaptive Force Control for Security Tele-Surgery - Université Paris-Est-Créteil-Val-de-Marne
Journal Articles ACM Transactions on Multimedia Computing, Communications and Applications Year : 2021

Output-Bounded and RBFNN-Based Position Tracking and Adaptive Force Control for Security Tele-Surgery

Ting Wang
  • Function : Author
Xiangjun Ji
  • Function : Author
Aiguo Song
  • Function : Author
Huimin Lu
  • Function : Author
Ramon Monero
  • Function : Author

Abstract

In security e-health brain neurosurgery, one of the important processes is to move the electrocoagulation to the appropriate position in order to excavate the diseased tissue. 1 However, it has been problematic for surgeons to freely operate the electrocoagulation, as the workspace is very narrow in the brain. Due to the precision, vulnerability, and important function of brain tissues, it is essential to ensure the precision and safety of brain tissues surrounding the diseased part. The present study proposes the use of a robot-assisted tele-surgery system to accomplish the process. With the aim to achieve accuracy, an output-bounded and RBF neural network–based bilateral position control method was designed to guarantee the stability and accuracy of the operation process. For the purpose of accomplishing a minimal amount of bleeding and damage, an adaptive force control of the slave manipulator was proposed, allowing it to be appropriate to contact the susceptible vessels, nerves, and brain tissues. The stability was analyzed, and the numerical simulation results revealed the high performance of the proposed controls.
No file

Dates and versions

hal-04317406 , version 1 (01-12-2023)

Identifiers

Cite

Ting Wang, Xiangjun Ji, Aiguo Song, Kurosh Madani, Amine Chohra, et al.. Output-Bounded and RBFNN-Based Position Tracking and Adaptive Force Control for Security Tele-Surgery. ACM Transactions on Multimedia Computing, Communications and Applications, 2021, 17 (2s), pp.1-15. ⟨10.1145/3394920⟩. ⟨hal-04317406⟩

Collections

LISSI UPEC
8 View
0 Download

Altmetric

Share

More