Online Teaching

Assistant Professor

GITAM College of Engineering,Pydah college of Engineering, India

Jul 2005 - Feb 2008

Electrical and Electronic measurements and Instrumentation, Industrial Instrumentation, Powerplant Instrumentation, Electronic Devices and Circuits, Microprocessors and Interfacing, Process Control, Random Vriables and stochastic Process, Telemetry and tele control

M.E

Anna University, India

Aug 2003 - May 2005

B.Tech

Jawaharlal Nehru Technological University, India

Dec 1999 - May 2003

National workshop on “Intelligent Sensors and Control Engineering”

Andaman and Nicobar Islands, India

Year Of Passing: 2006

National workshop on “Advances in Sensors and Applications”(WASA)

Andhra Pradesh, India

Year Of Passing: 2006

This paper deals with the Robot localization problem which is the fundamental problem in making robot truly autonomous. The robots have to use sensors, instrument and environmental information to find its location. There is existence of errors in the measurements which results in an inaccurate localization. These uncertain information need to be combined in an optimal way to obtain the best state estimate. Sensor fusion provides a technique to combine information from different sensors in providing a best estimate of the robot's state. The uncertain information from different sensors can be fused by extended kalman filter. In this project the localization problem is discussed as a case of state estimation problem and the optimal solution to estimate the state is implemented using Extended Kalman Filter. Kalman Filters are a classical approach to estimating states of noisy systems in noisy environments. The nonlinear system and measurement models are discussed and the behaviour of the extended kalman filter for irregular and circular paths is studied by simulation using Matlab software.