title: Nanorobotics control design: a collective behavior approach for medicine.
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.
authors.affiliation: Computational Nanomechatronics Lab, Center for Automation in Nanobiotech, Sao Paulo SP 01540-000, Brazil. adrianocavalcanti@canbiotechnems.com
authors.forename: Adriano
authors.initials: A
authors.lastname: Cavalcanti
authors.forename: Robert A
authors.initials: RA
authors.lastname: Freitas
mesh_terms: D000465:Algorithms; D001698:Biomedical Engineering / Q000295:instrumentation* / Q000379:methods / Q000639:trends; D003198:Computer Simulation; D017076:Computer-Aided Design; D003299:Cooperative Behavior; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005246:Feedback; D008846:Micromanipulation / Q000295:instrumentation* / Q000379:methods / Q000639:trends; D008962:Models, Theoretical; D036103:Nanotechnology / Q000295:instrumentation* / Q000379:methods / Q000639:trends; D012371:Robotics / Q000295:instrumentation* / Q000379:methods / Q000639:trends