— We present a new motion planning framework that explicitly considers uncertainty in robot motion to maximize the probability of avoiding collisions and successfully reaching a ...
We use a constrained optimization framework to derive fundamental scaling laws for both unstructured sensor networks (which use blind sequential search for querying) and structure...
We propose a data model and a few algebraic operations that provide semantic foundation to multidimensional databases. The distinguishing feature of the proposed model is the symm...
—We propose a probabilistic formulation of joint silhouette extraction and 3D reconstruction given a series of calibrated 2D images. Instead of segmenting each image separately i...
Static analyses provide the semantic foundation for tools ranging from optimizing compilers to refactoring browsers and advanced debuggers. Unfortunately, developing new analysis ...