Automated Guided Vehicle Navigated using Fuzzy Cognitive Maps and Intelligent Space

Intelligent Automated Guided Vehicle using Visual Servoing

Fuzzy Cognitive Maps and Intelligent Decision Support

Cognitive maps have been utilised in decision analysis in the past. More recently fuzzy cognitive maps (FCMs) have been proposed as an alternative to knowledge-based expert systems for representing and analysing complex systems. Increasing interest in adaptive systems, in the form of artificial neural networks, has also focussed attention on FCMs. This paper presents an overview of the evolutio...

Intelligent Automated Guided Vehicle Controller with Reverse Strategy

This paper describes the intelligent Automated Guided Vehicle (AGV) control system using Fuzzy Rule Interpolation (FRI) method. The AGV used in this paper is a virtual vehicle simulated using computer. The purpose of the control system is to control the simulated AGV by moving along the given path towards a goal. Some obstacles can be placed on or near the path to increase the difficulties of t...

AGV (automated guided vehicle) robot: Mission and obstacles in design and performance

The AGV (automated guided vehicle) was introduced in UK in 1953 for transporting. But nowadays, due to their high efficiency, flexibility, reliability, safety and system scalability, they are used in various application in industries. In brief, the AGV robot is a system which typically made up of vehicle chassis, embedded controller, motors, drivers, navigation and collision avoidance sensors, ...

Fuzzy Cognitive Maps: a model for intelligent supervisory control systems

Ž . Fuzzy Cognitive Maps FCMs is a new approach in modelling the behaviour and operation of complex systems. FCMs are proposed to be used in the modelling of control systems and particularly in the modelling of the upper part or supervisor of a hierarchical control system. The description and the formulation of FCM are examined, moreover a process control problem is presented and its model and ...