Current issues in sampling-based motion planning

Stephen R. Lindemann, Steven M. LaValle

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we discuss the field of sampling-based motion planning. In contrast to methods that construct boundary representations of configuration space obstacles, sampling-based methods use only information from a collision detector as they search the configuration space. The simplicity of this approach, along with increases in computation power and the development of efficient collision detection algorithms, has resulted in the introduction of a number of powerful motion planning algorithms, capable of solving challenging problems with many degrees of freedom. First, we trace how sampling-based motion planning has developed. We then discuss a variety of important issues for sampling-based motion planning, including uniform and regular sampling, topological issues, and search philosophies. Finally, we address important issues regarding the role of randomization in sampling-based motion planning.

Original languageEnglish (US)
Pages (from-to)36-54
Number of pages19
JournalSpringer Tracts in Advanced Robotics
Volume15
DOIs
StatePublished - Jan 1 2005

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Artificial Intelligence

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