A Multi-modal Perception based Architecture for a Non-intrusive Domestic Assistant Robot

Christophe Mollaret (1) , Alhayat Ali Mekonnen (1) , Julien Pinquier (2) , Frédéric Lerasle (1, 3) , Isabelle Ferrané (2)

1 LAAS-RAP - Équipe Robotique, Action et Perception
2 IRIT-SAMoVA - Équipe Structuration, Analyse et MOdélisation de documents Vidéo et Audio
3 UT3 - Université Toulouse III - Paul Sabatier

We present a multi-modal perception based architecture to realize a non-intrusive domestic assistant robot. The realized robot is non-intrusive in that it only starts interaction with a user when it detects the user's intention to do so automatically. All the robot's actions are based on multi-modal perceptions, which include: user detection based on RGB-D data, user's intention-for-interaction detection with RGB-D and audio data, and communication via speech recognition. The utilization of multi-modal cues in different parts of the robotic activity paves the way to successful robotic runs.

Mots clés: Magnetic heads; Head; Detectors; Robot kinematics; Speech recognition; Speech

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]; Robotique [cs.RO]

Christophe Mollaret, Alhayat Ali Mekonnen, Julien Pinquier, Frédéric Lerasle, Isabelle Ferrané. A Multi-modal Perception based Architecture for a Non-intrusive Domestic Assistant Robot. 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI 2016), ACM; IEEE, Mar 2016, Christchurch, New Zealand. pp.481-482, ⟨10.1109/HRI.2016.7451816⟩. ⟨hal-01296633⟩