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- W1413971837 abstract "During the last few years mobile robots got more and more important to solve different tasks in outdoor and indoor environments. To solve these tasks one very essential issue is to get from one point A to another point B as fast as possible. To find the least expensive route to the goal the pathfinding process needs a full state space information about the environment. With this information we can use optimally efficient algorithms like A* to find the route, but this might be very expensive on memory usage and time response. therefore we need to use other data structures to represent the whole information about the environment. This paper shows how the usage of quadtrees improves performance in terms of computation speed, memory requirements and path length." @default.
- W1413971837 created "2016-06-24" @default.
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- W1413971837 date "2011-01-01" @default.
- W1413971837 modified "2023-10-02" @default.
- W1413971837 title "Using Quadtrees for Realtime Pathfinding in Indoor Environments" @default.
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- W1413971837 doi "https://doi.org/10.1007/978-3-642-27272-1_6" @default.
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