This document formalizes and discusses the implementation of a new, more efficient probabilistic plan recognition algorithm called Yet Another Probabilistic Plan Recognizer, (Yapp...
Christopher W. Geib, John Maraist, Robert P. Goldm...
— This paper presents a method to recognize and generate sequential motions for object manipulation such as placing one object on another or rotating it. Motions are learned usin...
This paper develops Probabilistic Hybrid Action Models (PHAMs), a realistic causal model for predicting the behavior generated by modern concurrent percept-driven robot plans. PHA...
Abstract-- This paper presents a novel framework for integrating fundamental tasks in robotic navigation through a statistical inference procedure. A probabilistic model that joint...
— We present a probabilistic architecture for solving generically the problem of extracting the task constraints through a Programming by Demonstration (PbD) framework and for ge...