TY - GEN
T1 - Behavior Recognition in Mobile Robots Using Symbolic Dynamic Filtering and Language Measure
AU - Mallapragada, Goutham
AU - Ray, Asok
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
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U2 - 10.1109/ACC.2009.5160145
DO - 10.1109/ACC.2009.5160145
M3 - Conference contribution
AN - SCOPUS:70449686223
SN - 9781424445240
T3 - Proceedings of the American Control Conference
SP - 1329
EP - 1334
BT - 2009 American Control Conference, ACC 2009
T2 - 2009 American Control Conference, ACC 2009
Y2 - 10 June 2009 through 12 June 2009
ER -