Title :
Nanorobotics control design: a collective behavior approach for medicine
Author :
Cavalcanti, Antonio ; Freitas, Robert A., Jr.
Author_Institution :
Comput. Nanomechatronics Lab., Center for Autom. in Nanobiotech, Sao Paulo, Brazil
fDate :
6/1/2005 12:00:00 AM
Abstract :
The authors present a new approach using genetic algorithms, neural networks, and nanorobotics concepts applied to the problem of control design for nanoassembly automation and its application in medicine. As a practical approach to validate the proposed design, we have elaborated and simulated a virtual environment focused on control automation for nanorobotics teams that exhibit collective behavior. This collective behavior is a suitable way to perform a large range of tasks and positional assembly manipulation in a complex three-dimensional workspace. We emphasize the application of such techniques as a feasible approach for the investigation of nanorobotics system design in nanomedicine. Theoretical and practical analyses of control modeling is one important aspect that will enable rapid development in the emerging field of nanotechnology.
Keywords :
control system synthesis; genetic algorithms; medical robotics; mobile robots; nanotechnology; neural nets; virtual reality; genetic algorithm; medicine; nanoassembly automation; nanorobotics control design; nanotechnology; neural networks; virtual environment; Assembly; Automatic control; Control design; Design automation; Genetic algorithms; Medical control systems; Medical simulation; Nanotechnology; Neural networks; Virtual environment; Biomedical engineering; control systems; mechatronics; nanotechnology; virtual reality; Algorithms; Biomedical Engineering; Computer Simulation; Computer-Aided Design; Cooperative Behavior; Equipment Design; Equipment Failure Analysis; Feedback; Micromanipulation; Models, Theoretical; Nanotechnology; Robotics;
Journal_Title :
NanoBioscience, IEEE Transactions on
DOI :
10.1109/TNB.2005.850469