In this paper, we exploit a fuzzy controller on a flexible bevel-tip needle to manipulate the needle's base in order to steer its tip in a preset obstacle-free and target-tracking path. Although the needle tends to follow a curvature path, spinning the needle with an extremely high rotational velocity makes it symmetric with respect to the tissue to follow a straight path. The fuzzy controller determines an appropriate spinning to generate the planned trajectory and, the closed-loop system tries to match the needle body with that trajectory. The swine's brain tissue model, extracted from an in-vitro experimental setup, is a non-homogenous, uncertain and fast-updatable network to model real tissues, needle and their interactions providing the essential visual feedback for the control system. The simulation results illustrate a precise path tracking of the bevel-tip needle based on the fuzzy controller's commands with two degrees of freedom.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1109/IEMBS.2009.5333473 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Introducing an integrated approach for fire safety assessment in healthcare facilities by interval valued neutrosophic-AHP and Fuzzy Inference System.
Heliyon
January 2025
Department of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Fire safety in healthcare facilities is extremely important due to limited evacuation capacity of occupants. Therefore, poor fire safety precautions lead to more fatalities and financial losses. This study introduces an effective fire risk management approach for healthcare buildings utilizing an interval valued neutrosophic-fuzzy framework.
View Article and Find Full Text PDFFuzzy logic modelling of the pollution pattern of potentially toxic elements and naturally occurring radionuclide materials in quarry sites in Ogun State, Nigeria.
Environ Geochem Health
January 2025
Department of Chemistry, Chulalongkorn University, Bangkok, Thailand.
The accumulation pattern of some inorganic pollutants in quarry sites around Ogun State was modeled using a Fuzzy comprehensive assessment (FCA). Potentially toxic elements (PTEs) and naturally occurring radionuclides materials (NORMs) were assessed from soil samples collected from ten quarry sites in three districts (Odeda, Ajebo, and Ijebu Ode) in Ogun State. Three (3) NORMs ( K, U, Th) were assessed using gamma spectrometer with a NaI detector while ten (10) PTEs (As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) were determined by digestion method using Inductively coupled plasma optical emission spectrophotometer.
View Article and Find Full Text PDFA novel Complex q-rung orthopair fuzzy Yager aggregation operators and their applications in environmental engineering.
Heliyon
January 2025
Department of Mathematics and Statistics, International Islamic University Islamabad, Pakistan.
Improving human health and comfort in buildings requires efficient temperature regulation. Temperature control system has a significant contribution in minimizing the impact of climate change. Temperature control system is used in industry to control temperature.
View Article and Find Full Text PDFFuzzy reinforcement learning based control of linear systems with input saturation.
ISA Trans
January 2025
Toronto Metropolitan University, Toronto, Canada. Electronic address:
This research introduces an innovative approach to optimal control for a class of linear systems with input saturation. It leverages the synergy of Takagi-Sugeno (T-S) fuzzy models and reinforcement learning (RL) techniques. To enhance interpretability and analytical accessibility, our approach applies T-S models to approximate the value function and generate optimal control laws while incorporating prior knowledge.
View Article and Find Full Text PDFA Fuzzy Control Strategy for Multi-Goal Autonomous Robot Navigation.
Sensors (Basel)
January 2025
Department of Product & Systems Design Engineering, University of the Aegean, 84100 Syros, Greece.
This paper addresses the complex problem of multi-goal robot navigation, framed as an NP-hard traveling salesman problem (TSP), in environments with both static and dynamic obstacles. The proposed approach integrates a novel path planning algorithm based on the Bump-Surface concept to optimize the shortest collision-free path among static obstacles, while a Genetic Algorithm (GA) is employed to determine the optimal sequence of goal points. To manage static or dynamic obstacles, two fuzzy controllers are developed: one for real-time path tracking and another for dynamic obstacle avoidance.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!