Behavior Recognition in Mobile Robots Using Symbolic Dynamic Filtering and Language Measure

Goutham Mallapragada, Asok Ray

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

Abstract

This paper addresses dynamic data-driven signature detection in mobile robots. The core concept of the paper is built upon the principles of Symbolic Dynamic Filtering (SDF) that has been recently reported in literature for extraction of relevant information (i.e., features) in complex dynamical systems. The objective here is to identify the robot behavior in real time as accurately as possible. Two different approaches to classifier design are presented in the paper; the first one is Bayesian and the second is based on measures of formal languages. The proposed methods have been experimentally validated on a networked robotic testbed to detect and identify the type and motion profile of the robots under consideration.

Original languageEnglish (US)
Title of host publication2009 American Control Conference, ACC 2009
Pages1329-1334
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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    Mallapragada, G., & Ray, A. (2009). Behavior Recognition in Mobile Robots Using Symbolic Dynamic Filtering and Language Measure. In 2009 American Control Conference, ACC 2009 (pp. 1329-1334). [5160145] (Proceedings of the American Control Conference). https://doi.org/10.1109/ACC.2009.5160145