V*: A robot path planning algorithm based on renormalised measure of probabilistic regular languages

Ishanu Chattopadhyay, Goutham Mallapragada, Asok Ray

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

This article introduces a novel path planning algorithm, called , that reduces the problem of robot path planning to optimisation of a probabilistic finite state automaton. The -algorithm makes use of renormalised measure of regular languages to plan the optimal path for a specified goal. Although the underlying navigation model is probabilistic, the -algorithm yields path plans that can be executed in a deterministic setting with automated optimal trade-off between path length and robustness under dynamic uncertainties. The -algorithm has been experimentally validated on Segway Robotic Mobility Platforms in a laboratory environment.

Original languageEnglish (US)
Pages (from-to)849-867
Number of pages19
JournalInternational Journal of Control
Volume82
Issue number5
DOIs
StatePublished - May 1 2009

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications

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