A STUDY OF INSECT BRAIN USING ROBOTICS AND NEURAL NETWORKS

Abstract

Genetic algorithms have been used to construct a neural model for insect path integration in order to help understand how insects navigate.Some experiments have been carried out to simulate navigation using autonomous robots that hoped to not only explain certain factors relevant to insect navigation but also increased our knowledge toward the understanding of insect/robot modular systems.In this paper the neural model using the brain of an insect have been proposed and the concept that a simple model is best could give rise to a new generation of intelligent machines. The idea of the artificial neural network to help describe how an insect’s “cognitive map” is used for navigation has been designed for use on robot control as a decentralized model, chemical intelligence and in optical predictive models among others.Technical advances in analog integrated circuitry along with micro electro mechanical systems (MEMS) have given rise to compact systems (with hardware inspired architecture HNN or Hardware Neural Networks) that may someday help us understand how insects do what they do so well.Anyhow a variety of basic insect behaviours have inspired successful robot implementations,more complex capabilities in these ‘simple’ animals are often changed.By looking into the general design of their nervous systems,we will be able to know how to integrate behaviours,perform pattern recognition, and combine many sensory inputs in tasks such as Navigation.Brain Hybrid system etc,which is compared with the real time insect.