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EN
The second most important function of a warehouse, apart from the storing of goods, is internal transport with a focus on time-effectiveness. When there is a time gap between the production and export of products, the goods need to be stored until they are dispatched to the consumers. An important problem that concerns both large and small warehouses is the selection of priorities, that is handling the tasks in order of importance. Another problem is to identify the most efficient routes for forklift trucks to transport goods from a start-point to a desired destination and prevent the routes from overlapping. In automated warehouses, the transport of objects (the so called pallets of goods) is performed by machines controlled by a computer instead of a human operator. Thus, it is the computer, not the man, that makes the difficult decisions regarding parallel route planning, so that the materials are transported within the warehouse in near-optimal time. This paper presents a method for enhancing this process.
EN
This paper presents an original method for nonholonomic mobile robot path planning. The method is based on A* searching of a graph built in a configuration space. Very good heuristic approximation of the real cost of the path accelerates path searching significantly. Due to dynamic modifications of the graph, the path replanning procedure is much faster than brute-force replanner. The paper presents general assumptions of the method, detailed algorithms of important procedures (especially the path replanning procedure) and a new form of configuration space and open list. The simulation and experimental tests on car-like robot as well as the comparisons of this method to the others are also included.
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