We present a general-purpose framework for updating a robot’s observation model within the context of planning and execution. Traditional plan execution relies on monitoring plan...
Sonia Chernova, Elisabeth Crawford, Manuela M. Vel...
We investigate the problem of learning action effects in partially observable STRIPS planning domains. Our approach is based on a voted kernel perceptron learning model, where act...
We present a logical approach to plan recognition that builds on Kautz's theory of keyhole plan recognition, defined as the problem of inferring descriptions of high-level pl...
Strong Cyclic Planning aims at generating iterative plans that only allow loops so far as there is a chance to reach the goal. The problem is already significantly complex for ful...
Piergiorgio Bertoli, Alessandro Cimatti, Marco Pis...
— In this work, we have extended the concept of constrained motion control of robots to surgical tasks that require multiple robots. We present virtual fixtures to guide the mot...