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Intelligent semi-autonomous vehicles in materials handling

Objectif


Foreseen Results

Virtual engineering for industrial mobile robotics/vehicles; a virtual design environment is used for pre-emptive learning / training of intelligent semi-autonomous human guided vehicles and the optimisation of operation strategies.
Advanced control architectures for intelligent semi-autonomous vehicles and intelligent guided vehicles.
New smart sensing techniques for industrial mobile robotics/vehicles.
A fundamentally new approach in building the control and sensing infrastructures for mobile vehicles applying field-bus type control networks
The primary aim of this research is to improve the operation, safety, self protection, efficiency and flexibility of semi-autonomous guided vehicles / assembly carriers through intelligent control and smart sensing techniques in materials handling and related applications. This will lead to safer, highly effective and responsive man-in-the-loop materials handling in manufacturing environments (e.g. automotive assembly) and hazardous environments (e.g. nuclear plants, mine clearance, bomb disposal, etc.).

Manufacturing industry and other industrial sectors require the extensive movement of products, tools and materials through out the production process. Materials handling is therefore an extremely important aspect of the overall manufacturing process which adds value by changing the temporal and spatial arrangement of products and materials inline with manufacturing goals. Assembly carriers and guided mobile robots are used to meet some of the materials handling needs, particularly in industries such as automotive manufacturing where the product and materials tend to be large and heavy which are difficult to manipulate by other means. Such handling systems need to be highly flexible to meet changing production schedules and transportation routings. The concept of semi-autonomous vehicles is both novel and timely for manufacturing and other sectors in meeting the need for improved performance, safer operation, flexibility and ease of use. Semi-autonomous intelligent vehicles (with remote operators) also offer great potential in hazardous environments in applications such as nuclear plant maintenance/decommissioning, surveillance, mine clearance, and bomb disposal.
There will be four main aspects to the research proposed here, namely:
the development of a reactive behavioral control architecture suitable for 'semi-autonomous guided vehicles' (such as assembly carriers) and "intelligent guided vehicles" (capable of navigating locally from the guide wire to avoid obstacles in the manufacturing plant or related environment) to provide easier use, increased self protection, safer operation and improved functionality.
the creation of "virtual environments" to allow the "pre-emptive learning" of behaviors for the semi- autonomous vehicles (e.g. to reduce dramatically on-site training and to improve the operation of the vehicle). Computer aided graphical simulation tools will be created to model the vehicle, the sensors, its environment and its interaction in an event based emulation that closely matches the real application environment.
the integration and development of distributed control and sensing architectures for"semi-autonomous guided vehicles" and "intelligent wire guided vehicles". The resulting integrated architectures will embody smart sensing and control objects which are both co-operative and autonomous.
the development of smart sensors appropriate for intelligent vehicle guidance systems (in particular novel digital signal processing techniques and piezo-materials for ultrasonic sensors will be studied).

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Coordinateur

DE MONTFORT UNIVERSITY
Contribution de l’UE
Aucune donnée
Adresse
The Gateway
LE1 9BH LEICESTER
Royaume-Uni

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