Robust Belief Road Map: Path Planning under Intermittent Sensing

May 13, 2013, HFH 4164

Shaunak Bopardikar


Map-based, GPS-denied navigation often relies on the measurement of environmental features to perform state estimation. While producing consistent estimates in the presence of sensor noise is of primary concern in designing a state estimator, an important related question is how to navigate robustly when a sensor does not produce a measurement at all. This could be caused either due to adverse environmental conditions that prevent the sensors from making measurements or due to fundamental limitations of the sensors. Examples include RF-based ranging devices that intermittently receive signal from beacons because of obstacles; the misdetection of features by a camera system in detrimental lighting conditions; or a LIDAR sensor that is pointed at a glass-based material such as a window. In this talk, I will present an extension to the recent body of work on planning under uncertainty to include the fact that sensors may not provide any measurement owing to misdetection. We will begin with an analytical characterization of the performance of a state estimator under sensor misdetection occurring stochastically over time in the environment. We will then see how this bound can be used to enhance computational efficiency within a sample-based path planning algorithm to produce a path that minimizes goal-state uncertainty under such a stochastic model of misdetection. Numerical results demonstrate the benefit of the approach, and comparisons are made with the state of the art in path planning under state uncertainty.

Speaker's Bio

Shaunak Bopardikar is a Senior Research Scientist with the Embedded Systems and Networks group of United Technologies Research Center Inc. (UTRC), Berkeley, CA. He currently contributes in the development of autonomous motion planning and control, cyber-physical security and big data computation and optimization problems. He received B.Tech. and M.Tech. degrees in Mechanical Engineering from Indian Institute of Technology Bombay in 2004, and a Ph.D. degree in Mechanical Engineering from the University of California, Santa Barbara in 2010. He was a postdoctoral researcher with the Electrical and Computer Engineering Department at University of California Santa Barbara from 2010 to 2011, before joining UTRC. He is a member of IEEE, IEEE Control System Society and IEEE Communications Society.

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