Neural motion and evolutionary decision in robotic competition applied for molecular machine system design

Abstract

Summary form only given. The author presents a new approach within advanced graphics simulations for the problem of nano-assembly automation and its application for nanomedicine. The problem under study concentrates its main focus on the design of autonomous nanorobots for assembly manipulation and the use of evolutionary competitive agents as a suitable way to warranty the robustness of such proposed model. Furthermore, the work presents also the use of neural networks as the most practical approach for the problem of robot motion optimisation using a sensor based system. Thereby the paper addresses distinct aspects of the main techniques required to achieve a successful nano-planning system design and its simulation with a real time 3D visualization.