Abstract
As industry moves toward an era of complete automation and ‘mass customisation’, automated guided vehicles (AGVs) are used as material handling systems. However, the current techniques that provide navigation, control, and manoeuvrability of automated guided vehicles threaten to create bottlenecks and inefficiencies in manufacturing environments that strive towards the optimisation of part production. This paper proposes a decentralised localisation technique for an automated guided vehicle without any non-holonomic constraints. Incorporation of these vehicles into the material handling system of a computer-integrated manufacturing environment would increase the characteristics of robustness, efficiency, flexibility, and advanced manoeuvrability. OPSOMMING
Highlights
In order to gain a competitive advantage in today’s high-tech industries, part manufacturers have to take advantage of new technologies. These modern technologies attempt to combine the idea of flexible manufacturing systems (FMS) with well-known mass production manufacturing techniques
This paper aims to introduce a navigation technique for an omnidirectional robot using the discrete Kalman filter
The extended Kalman filter was implemented as the probabilistic localisation technique of an omnidirectional mobile robot
Summary
In order to gain a competitive advantage in today’s high-tech industries, part manufacturers have to take advantage of new technologies These modern technologies attempt to combine the idea of flexible manufacturing systems (FMS) with well-known mass production manufacturing techniques. By taking advantage of modern and well-known navigation techniques – thereby providing greatly improved flexibility, robustness, and efficiency – automated guided vehicles will become the popular choice in a ‘mass customisation’ manufacturing environment. This paper aims to introduce a navigation technique for an omnidirectional robot using the discrete Kalman filter. It will greatly increase the efficiency, robustness, flexibility, and manoeuvrability of automated guided vehicles in a part manufacturing environment
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