— Computationally efficient motion planning must avoid exhaustive exploration of configuration space. We argue that this can be accomplished most effectively by carefully balan...
— Modeling robot motion planning with uncertainty in a Bayesian framework leads to a computationally intractable stochastic control problem. We seek hypotheses that can justify a...
Andrea Censi, Daniele Calisi, Alessandro De Luca, ...
—Enterprise computing is moving towards more open, collaborative systems. Joining a business network must be made efficient, despite the technical and semantic interoperability ...
Abstract—An overview of recent advances in secure peerto-peer networking is presented, toward enforcing data integrity, confidentiality, availability, and access control policie...
— Randomly expanding trees are very effective in exploring high-dimensional spaces. Consequently, they are a powerful algorithmic approach to sampling-based single-query motion p...