Multi-sensor system of intellectual handling robot control on the basis of collective learning paradigm

Abstract

Approaches based on self-learning and self-organization of collective of interacting intellectual agents (sensor channels, units of neural networks structures and others DAI-forming entities) are recently more often used in development of collective recognition and control systems. Approaches to organization of co-learning and mutual learning on the basis of reliability coefficients of sensor data are described. Approach to development of recognizing multi-sensor system on a basis of two-dimensional two-level neural networks is offered. Scheme of multi-unit manipulators control on a basis of neural approach are described. The results are used for development of robotics systems for operation in extreme (underwater) conditions. © 2011 Springer-Verlag Berlin Heidelberg.