Planning Algorithms: Introductory Material
Citations
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Cites background or methods or result from "Planning Algorithms: Introductory M..."
...1996, 1998) and rapidly-exploring random trees (RRTs) (Kuffner and LaValle 2000; LaValle and Kuffner 2001; LaValle 2006)....
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...In particular, the following criteria are of particular interest: • k-nearest (s)PRM: Choose the nearest k neighbors to the vertex under consideration, for a given k (a typical value is reported as k = 15 (LaValle 2006))....
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...Our results also extend to the rapidly exploring random dense trees (see, e.g., LaValle 2006), which are slightly modified versions of the RRTs that do not require tuning any prespecified parameters such as η in this case....
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...The robotic motion planning problem has received a considerable amount of attention, especially over the last decade, as robots started becoming a vital part of modern industry as well as our daily life (Latombe 1991; Choset et al. 2005; LaValle 2006)....
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...Note that in the discussion of variable-radius PRM in LaValle (2006), it is suggested that the radius be chosen as a function of sample dispersion....
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References
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"Planning Algorithms: Introductory M..." refers background or methods in this paper
...This can also be justified by using Shannon’s entropy measure from information theory [50, 250, 866]....
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...This brings it closer to the Kolmogorov complexity [250, 633] of the state transition graph, which is the shortest bit size to which it can possibly be compressed and then fully recovered by a Turing machine....
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37,989 citations
"Planning Algorithms: Introductory M..." refers background or methods in this paper
...It turns out that a single trial can actually yield update values for multiple states [75, 98]....
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...It was developed and used primarily by machine learning researchers [19, 75], and therefore this section is called reinforcement learning....
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22,704 citations
"Planning Algorithms: Introductory M..." refers methods in this paper
...The result is the well-known Dijkstra’s algorithm for finding single-source shortest paths in a graph [275], which is a special form of dynamic programming....
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18,761 citations
"Planning Algorithms: Introductory M..." refers background in this paper
...In other settings, Markovian could mean a dependency on a small number of stages, or even a local dependency in terms of spatial relationships, as in a Markov random field [233, 379]....
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