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[citace_text] => GULINA, I. Motion planning in challenging environments using rapidly-exploring random trees. In 19th International Conference on Soft Computing, MENDEL 2013. Mendel Journal series. 2013. 2013. no. 1, p. 153-160. ISBN: 978-80-214-4755-4. ISSN: 1803-3814.
[citace_html] => GULINA, I. Motion planning in challenging environments using rapidly-exploring random trees. In 19th International Conference on Soft Computing, MENDEL 2013. Mendel Journal series. 2013. 2013. no. 1, p. 153-160. ISBN: 978-80-214-4755-4. ISSN: 1803-3814.
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author="Irina {Gulina}",
title="Motion planning in challenging environments using rapidly-exploring random trees",
booktitle="19th International Conference on Soft Computing, MENDEL 2013",
year="2013",
series="2013",
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number="1",
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[nazev_en] => Motion planning in challenging environments using rapidly-exploring random trees
[popis_en] => This paper presents an efficient approach to trajectory planning for a holonomic mobile robot moving in static challenging environments including, for example, cluttered environments and spaces with narrow passages. It is an extension of the connect version of Rapidly-exploring random trees (RRT-connect) algorithm. The main idea presented here is to store randomly sampled configuration states which can not be reached because of collision, and then set them as roots to grow other random trees. It presumes growing of many trees in different hard to reach regions of environment to find bridges between them. Both simulation and experimental results demonsrate that it reduces the complexity of the original problem and thus resulting in fast space covering and increase the probability of finding the goal state
[klicova_slova_en] => Rapidly-exploring random trees (RRTs) algorithm, multi-trees, motion planning, holonomic mobile robot
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