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Algorithmic Motion Planning: The Randomized Approach

  • S. Carpin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4123)

Abstract

Algorithms based on randomized sampling proved to be the only viable algorithmic tool for quickly solving motion planning problems involving many degrees of freedom. Information on the configuration space is acquired by generating samples and finding simple paths among them. Paths and samples are stored in a suitable data structure. According to this paradigm, in the recent years a wide number of algorithmic techniques have been proposed and some approaches are now widely used. This survey reviews the main algorithms, outlining their advantages and drawbacks, as well as the knowledge recently acquired in the field.

Keywords

Motion Planning Path Planning Medial Axis Rapidly Explore Random Tree Narrow Passage 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • S. Carpin

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