Adaptive Augmented Kalman Modeling for Embedded Autonomous Robot Systems under Wireless Sensor Network

  • Published : 2010.05.27

Abstract

This paper presents a Kalman filter based modeling algorithm for autonomous robots. State of the robot systems is measured by using embedded sensors and then carried to a host computer via ubiquitous sensor network (USN). We settle a linear state space motion equation for unknown system dynamics and modify a popular Kalman filter algorithm in deriving suitable parameter estimation mechanism. We conduct real-time experiment to test our proposed modeling algorithm where velocity state of the constructed robot is used as system observation.

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