Safe Multimodal Communication in Human-Robot Collaboration

TL;DR

This paper presents a framework for safe, multimodal human-robot communication using voice and gesture fusion, ensuring safety compliance and improved collaboration efficiency in industrial settings.

Contribution

It introduces a novel multimodal communication framework that combines voice and gesture inputs with safety regulation adherence for human-robot collaboration.

Findings

Multimodal communication improves information extraction for robot tasks.

The safety layer allows robots to adjust speed for operator safety.

Experimental validation shows enhanced collaboration efficiency.

Abstract

The new industrial settings are characterized by the presence of human and robots that work in close proximity, cooperating in performing the required job. Such a collaboration, however, requires to pay attention to many aspects. Firstly, it is crucial to enable a communication between this two actors that is natural and efficient. Secondly, the robot behavior must always be compliant with the safety regulations, ensuring always a safe collaboration. In this paper, we propose a framework that enables multi-channel communication between humans and robots by leveraging multimodal fusion of voice and gesture commands while always respecting safety regulations. The framework is validated through a comparative experiment, demonstrating that, thanks to multimodal communication, the robot can extract valuable information for performing the required task and additionally, with the safety layer, the robot can scale its speed to ensure the operator's safety.