Department of Computer, Control and Management Engineering

In the context of collaborative robotics, robots share the working space with humans and communication between the two parties is of utmost importance. While different modalities can be employed, speech represents a natural way of interaction for people. In this paper, we introduce a speech-based pipeline for collaborative robotics, specifically designed to operate in the context of precision agriculture. The system exploits frame semantics as a modality-independent way of representing information, which allows for easier management of the dialogue between the robot and the human. One of the key features of this pipeline is the utilization of various techniques from Natural Language Processing (NLP) to extract and manage frames.