— Algorithmic problem reduction is a fundamental approach to problem solving in many fields, including robotics. To solve a problem using this scheme, we must reduce the problem...
In this paper we present a probabilistic framework for the reduction in the uncertainty of a moving robot pose during exploration by using a second robot to assist. A Monte Carlo ...
Ioannis M. Rekleitis, Gregory Dudek, Evangelos E. ...
We propose a Bayesian framework for representing and recognizing local image motion in terms of two basic models: translational motion and motion boundaries. Motion boundaries are ...
Shrinking devices to the nanoscale, increasing integration densities, and reducing of voltage levels down to the thermal limit, all conspire to produce faulty systems. Frequent oc...
Kundan Nepal, R. Iris Bahar, Joseph L. Mundy, Will...
Human motion tracking is an important problem in computer vision. Most prior approaches have concentrated on efficient inference algorithms and prior motion models; however, few c...
Marek Vondrak, Leonid Sigal, Odest Chadwicke Jenki...