A Statistically Rigorous Analysis of 2D Path-Planning Algorithms

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[1] Muñoz, Pablo
[2] Barrero, David F.
[3] R-Moreno, María D.
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R-Moreno, María D. (mdolores@aut.uah.es) | 1600年 / Oxford University Press卷 / 58期
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Path-planning is a well-known studied problem in Artificial Intelligence. Given two points in a map; path-planning algorithms search for a path that joins those two points; avoiding obstacles. It is a challenging problem with important practical applications in a wide range of applications: autonomous mobile robotics; logistics or video games; just to mention some of them. Given its importance; it has attracted much research; resulting in a large number of algorithms; some classical; such as A∗; other more specialized; such as swarms. However; despite all the literature dedicated to this problem; the statistics used to analyze experimental results in most cases are naïve. In this paper; we position in favor of the need of incorporating stronger statistical methods in path-planning empirical research and promote a debate in the research community. To this end; we analyze some 2D-grid classical path-planning algorithms in discrete domains (i.e. A∗ and A∗ with post-processing) and more recent algorithms in continuous domains (i.e. Theta∗ and S-Theta∗). Given the differences of these algorithms; we study them under different criteria: Run-time; number of heading changes; number of expanded vertices and path-length. © The British Computer Society 2014. All rights reserved;
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