Home /Research /Intelligent System for Robotic Navigation Using ANFIS and ACOr
LEARNING

Intelligent System for Robotic Navigation Using ANFIS and ACOr

Malika Lazreg, Nacéra Benamrane

Year
2019
Citations
9

Abstract

In this article we propose an intelligent system for mobile robot navigation in different environments, using ANFIS and ACOr. This system is capable of ensuring to mobile robot to navigate by reacting to the various situations encountered in different environments. In a first step, we use the ANFIS controller (Adaptive network-based fuzzy inference system) in which the contribution of the fuzzy logic of TAKAJI-SUGENO is added to that of the neural networks in a suitable way. In the second step, the ant colony method in a continuous environment ACOr (Ant colony optimization for continuous domains) is grafted into the second layer of the ANFIS network for hybridization. Simulations of the movements of the robot and the graphic interfaces are realized under the C ++ language.

Keywords

Computer scienceArtificial intelligenceUnmanned surface vehicleAdaptive neuro fuzzy inference systemHuman–computer interactionSimulationMarine engineeringFuzzy control systemFuzzy logic

Related papers

Browse all LEARNING papers