Co-Speech Gestures for Human-Robot Collaboration

Abstract

Collaboration between human and robot requires effective modes of communication to assign robot tasks and coordinate activities. As communication can utilize different modalities, a multi-modal approach can be more expressive than single modal models alone. In this work we propose a cospeech gesture model that can assign robot tasks for humanrobot collaboration. Human gestures and speech, detected by computer vision and speech recognition, can thus refer to objects in the scene and apply robot actions to them. We present an experimental evaluation of the multi-modal co-speech model with a real-world industrial use case. Results demonstrate that multimodal communication is easy to achieve and can provide benefits for collaboration with respect to single modal tools.