Output-Bounded and RBFNN-Based Position Tracking and Adaptive Force Control for Security Tele-Surgery - Université Paris-Est-Créteil-Val-de-Marne Accéder directement au contenu
Article Dans Une Revue ACM Transactions on Multimedia Computing, Communications and Applications Année : 2021

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

Ting Wang
  • Fonction : Auteur
Xiangjun Ji
  • Fonction : Auteur
Aiguo Song
  • Fonction : Auteur
Huimin Lu
  • Fonction : Auteur
Ramon Monero
  • Fonction : Auteur

Résumé

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.
Fichier non déposé

Dates et versions

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

Identifiants

Citer

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
6 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More