Incremental low-discrepancy lattice methods for motion planning

Stephen R. Lindemann, Steven M Lavalle

Research output: Contribution to journalConference article

Abstract

We present deterministic sequences for use in sampling-based approaches to motion planning. They simultaneously combine the qualities found in many other sequences: i) the incremental and self-avoiding tendencies of pseudo-random sequences, ii) the lattice structure provided by multiresolution grids, and iii) low-discrepancy and low-dispersion measures of uniformity provided by quasi-random sequences. The resulting sequences can be considered as multiresolution grids in which points may be added one at a time, while satisfying the sampling qualities at each iteration. An efficient, recursive algorithm for generating the sequences is presented and implemented. Early experiments show promising performance by using the samples in search algorithms to solve motion planning problems.

Original languageEnglish (US)
Pages (from-to)2920-2927
Number of pages8
JournalProceedings - IEEE International Conference on Robotics and Automation
Volume3
StatePublished - Dec 9 2003
Event2003 IEEE International Conference on Robotics and Automation - Taipei, Taiwan, Province of China
Duration: Sep 14 2003Sep 19 2003

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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