Title
: A Robot Path Planning Algorithm Based On Renormalised Measure Of Probabilistic Regular Languages
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.
Year
DOI
Venue
2009
10.1080/00207170802343196
INTERNATIONAL JOURNAL OF CONTROL
Keywords
Field
DocType
path planning, language measure, discrete event systems, supervisory control
Motion planning,Mathematical optimization,Path length,Algorithm,Finite-state machine,Robustness (computer science),Probabilistic logic,Regular language,Deterministic system (philosophy),Mathematics,Probabilistic automaton
Journal
Volume
Issue
ISSN
82
5
0020-7179
Citations 
PageRank 
References 
7
0.55
5
Authors
3
Name
Order
Citations
PageRank
Ishanu Chattopadhyay1286.91
Goutham Mallapragada2233.07
Ray, A.3832184.32