We study proactive communicative behavior, where robots provide information to humans which may help them to achieve desired outcomes, or to prevent possible undesired ones. Proactive behavior in an under-addressed area in AI and robotics, and proactive human-robot communication is even more so. We will combine the past expertise of Sorbonne Univ. (intention recognition) and Orebro Univ. (proactive behavior) to define proactive behavior based on the understanding of user’s intentions, and then extend it to consider communicative actions based on second-order perspective awareness.

We propose an architecture able to (1) estimate the human's intention of goal, (2) infer robot’s and human’s knowledge about foreseen possible upcoming outcomes of intended goal, (3) detect opportunities for desirability of intended goal to robot be proactive, (4) select action from the listed opportunities. The theoretical underpinning of this work will contribute to the study of theory of mind in HRI.

Output

Jupyter Notebook / Google Colab that presents the code of proposed architecture and is able to provide plug and play interaction.

a manuscript describing the proposed architecture and initial findings of the experiment

Project Partners:

  • Sorbonne Université, Mohamed CHETOUANI
  • Örebro University (ORU), Alessandro Saffioti and Jasmin Grosinger

Primary Contact: Mohamed CHETOUANI, Sorbonne University