A Generic Model for Estimating User Intentions in Human-Robot Cooperation

The recognition of user intentions is an important feature for humanoid robots to make implicit and human-like interactions possible. In this paper, we introduce a formal view on user-intentions in human-machine interaction and how they can be estimated by observing user actions. We use Hybrid Dynamic Bayesian Networks to develop a generic model that includes connections between intentions, actions, and sensor measurements. This model can be used to extend arbitrary human-machine applications by intention recognition.