Optimal path-planning under finite memory obstacle dynamics based on probabilistic finite state automata models

Ishanu Chattopadhyay, Asok Ray

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The v*-planning algorithm is generalized to handle finite memory obstacle dynamics. A sufficiently long observation sequence of obstacle dynamics is algorithmically compressed via Symbolic Dynamic Filtering to obtain a probabilistic finite state model which is subsequently integrated with the navigation automaton to generate an overall model reflecting both navigation constraints and obstacle dynamics. A v*-based solution then yields a deterministic plan that maximizes the difference of the probabilities of reaching the goal and of hitting an obstacle. The approach is validated by simulated solution of dynamic mazes.

Original languageEnglish (US)
Title of host publication2009 American Control Conference, ACC 2009
Pages2403-2408
Number of pages6
DOIs
StatePublished - Nov 23 2009
Event2009 American Control Conference, ACC 2009 - St. Louis, MO, United States
Duration: Jun 10 2009Jun 12 2009

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2009 American Control Conference, ACC 2009
CountryUnited States
CitySt. Louis, MO
Period6/10/096/12/09

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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