During the last decade, incremental sampling-based motion planning algorithms, such as the Rapidly-exploring Random Trees (RRTs), have been shown to work well in practice and to po...
We describe a model-based construction of an online tester for black-box testing of implementation under test (IUT). The external behavior of the IUT is modeled as an output obser...
We propose a more robust robot programming by demonstration system planner that produces a reproduction path which satisfies statistical constraints derived from demonstration traj...
Abstract— We consider the problem of planning collisionfree motions for general (i.e., possibly nonholonomic) redundant robots subject to task space constraints. Previous approac...
— Rapidly-exploring Random Trees (RRTs) are widely used to solve large planning problems where the scope prohibits the feasibility of deterministic solvers, but the efficiency o...
Alexander C. Shkolnik, Matthew Walter, Russ Tedrak...