VISITOR PRESENTATION

DR. CLARK TAYLOR

TUESDAY, NOVEMBER 6, 2012 AT 1:00PM FLETCHER 290B

Clark Taylor is currently a senior electronics engineer with the Sensors Directorate, US Air Force Research Laboratory. He received his PhD in Electrical and Computer Engineering from the University of California, San Diego in 2004. He has published over 40 papers in the fields of digital video processing for unmanned aerial vehicles (UAVs), vision-based navigation, video communication, and digital systems design. Dr. Taylor is also an associate editor for the "IEEE Transactions on Circuits and Systems for Video Technology" and has served on the technical program committee for several conferences and workshops.

Significant improvements in the accuracy of navigation state estimation have been previously demonstrated through the fusion of inertial measurement unit (IMU) and visual sensor data in both GPS-denied and GPS-enabled scenarios. Despite this improved navigation state accuracy, several significant hurdles remain before widespread acceptance of vision-aided navigation can be achieved. One significant bottleneck is the lack of accurate information about the performance of the vision-aided navigation algorithms. Many vision-aided navigation algorithms are implemented using some form of the Bayesian estimatior. In this talk we discuss two possible sources of error in performance information from Bayesian estimators. First, a well-known problem with Kalman filters (a form a Bayesian estimation) is that the covariance estimates returned from the Kalman filter are inconsistent, i.e. the Kalman Filter estimates of uncertainty are significantly smaller than the true uncertainty achieved by the Kalman Filter. Second, the presence of outliers in any visual processing-based algorithm is not explicitly accounted for in the Bayesian estimator. Basic methods for overcoming these two shortcomings will be presented with preliminary results.

Presentation Topic: Consistent Bayesian Estimation