Probabilistic roadmaps for path planning in high-dimensional configuration spaces
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Cites methods from "Probabilistic roadmaps for path pla..."
...This limitation, lower-bound hardness results [24], and strong motivation to handle practical planning problems have stimulated the development and success of many path planning methods that use randomization (e.g., [1, 3, 4, 5, 7, 10, 11, 16, 15 , 17, 23, 26])....
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...The probabilistic roadmap approach was the first to address this problem [ 15 ]....
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...Randomized path planning algorithms have usually been designed for one of two contexts: singlequery planning, and multiple-query planning [ 15 ]....
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2,993 citations
Cites background or methods from "Probabilistic roadmaps for path pla..."
...In the probabilistic roadmap approach (Amato and Wu 1996; Kavraki et al. 1996), a graph is constructed in the configuration space by generating random configurations and attempting to connect pairs of nearby configurations with a local planner that will connect pairs of configurations....
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...For the purpose of discussion, we choose two different techniques that have been successful in recent years: randomized potential fields (e.g., Barraquand and Latombe 1991b; Challou et al. 1995) and probabilistic roadmaps (e.g., Amato and Wu 1996; Kavraki et al. 1996)....
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References
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"Probabilistic roadmaps for path pla..." refers background in this paper
...Local minima-free potential functions (also called navigation functions) have been defined in [6], [31], [ 46 ]....
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1,641 citations
"Probabilistic roadmaps for path pla..." refers methods in this paper
...First use the algorithm in [ 37 ] to produce the vertices of the obstacles in the link’s C-space....
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...space (C-space [ 37 ]) of the robot is stored as an undirected graph R. The configurations are the nodes of R and the paths computed by the local planner are the edges of R. The learning phase is concluded by some postprocessing of R to improve its connectivity....
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