Applications of Pulsed Neural Network Incorporating Short Term Synaptic Plasticity to Autonomous Mobile Robots

Abstract

We compare the performance of four types of controllers for an autonomous mobile robot through computer simulation. Each controller consists of different kinds of architectures of neural networks (NN). Four types of NNs are as follows: Sigmoid NN, Radial NN, pulsed NN (PNN), and PNN incorporating short term synaptic plasticity (PNNSSP). In computer simulation, parameters of NNs are adjusted using genetic algorithm. The results of computer simulation show that PNNSSP is more efficient than other typs of NNs for the controller of the autonomous mobile robot.