3 resultados para Traction vehicles

em Digital Peer Publishing


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At the Chair of Logistics Engineering, TU Dresden, a particular focus is research and development of magnetic traction sheaves. Therein the main fundamentals of these special sheaves are determined for applications in different fields such as elevators, several kinds of winches, hoists and cranes. In the current research project “energy balance of magnetic traction sheaves”, the dynamic behaviour of systems with magnetic traction sheaves was investigated. The research focused on theoretical and practical examinations of energy balance. Moreover, a new approach for dimensioning magnetic traction sheave systems is presented. It is a project of the Research Foundation Intralogistics / Material Handling and Logistics (IFL), which is funded through the AiF under the program of Industrial Collective Research for SMEs (IGF) by the Federal Ministry of Economics and Technology (BMWi).

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Indoor positioning is the backbone of many advanced intra-logistic applications. As opposed to unified outdoor satellite positioning systems, there are many different technical approaches to indoor positioning. Depending on the application, there are different trade-offs between accuracy, range, and costs. In this paper we present a new concept for a 4-degree-of-freedom (4-DOF) positioning system to be used for vehicle tracing in a logistic facility. The system employs optical data transmission between active infrastructure and receiver devices. Compared to existing systems, these optical technologies promise to achieve better accuracy at lower costs. We will introduce the positioning algorithm and an experimental setup of the system.

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To master changing performance demands, autonomous transport vehicles are deployed to make inhouse material flow applications more flexible. The socalled cellular transport system consists of a multitude of small scale transport vehicles which shall be able to form a swarm. Therefore the vehicles need to detect each other, exchange information amongst each other and sense their environment. By provision of peripherally acquired information of other transport entities, more convenient decisions can be made in terms of navigation and collision avoidance. This paper is a contribution to collective utilization of sensor data in the swarm of cellular transport vehicles.