Intelligent Human-Machine Interaction Based on Dynamic Bayesian Networks Probabilistic Intention Recognition

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Abstract

In this article, a novel human-machine interaction based on the machine intention recognition of the human is presented. This work is motivated by the desire that intelligent machines as robots imitate human-human interaction, that is to minimize the need for classical direct human-machine interface and communication. A philosophical and technical background for intention recognition is discussed. Here, the intention-action-state scenario is modified and modeled by Dynamic Bayesian Networks to facilitate for probabilistic intention inference. The recognized intention, then, drives the interactive behavior of the machine such that it complies with the human intention in light of the real state of the world. An illustrative example of a human commanding a mobile robot remotely is given and discussed in details.

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