A real time implementable all-pair dynamic planning algorithm for robot navigation based on the renormalized measure of probabilistic regular languages

Wei Lu, Ishanu Chattopadhyay, Goutham Mallapragada, Asok Ray

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

Abstract

The recently reported planning algorithm is modified to handle on-the-fly dynamic updates to the obstacle map. The modified algorithm called All-Pair-Dynamic-Planning(APDP), models the problem of robot path planning in the framework of finite state probabilistic automata and solves the all-pair planning problem in one setting. We use the concept of renormalized measure of regular languages to plan paths with automated trade-off between path length and robustness under dynamic uncertainties, from any starting location to any goal in the given map. The dynamic updating feature of APDP efficiently updates path plans to incorporate newly learnt information about the working environment.

Original languageEnglish (US)
Title of host publication2009 American Control Conference, ACC 2009
Pages5174-5179
Number of pages6
DOIs
Publication statusPublished - 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

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All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Lu, W., Chattopadhyay, I., Mallapragada, G., & Ray, A. (2009). A real time implementable all-pair dynamic planning algorithm for robot navigation based on the renormalized measure of probabilistic regular languages. In 2009 American Control Conference, ACC 2009 (pp. 5174-5179). [5160373] (Proceedings of the American Control Conference). https://doi.org/10.1109/ACC.2009.5160373