From Human Perception and Action Recognition to Causal Understanding of Human-Robot Interaction in Industrial Environments

Stefano Ghidoni, Matteo Terreran, Daniele Evangelista, Emanuele Menegatti, Christian Eitzinger, Enrico Villagrossi, Nicola Pedrocchi, Nicola Castaman, Marcin Malecha, Sariah Mghames, Luca Castri, Marc Hanheide and Nicola Bellotto
From Human Perception and Action Recognition to Causal Understanding of Human-Robot Interaction in Industrial Environments
Ital-IA 2022

Abstract

Human-robot collaboration is migrating from lightweight robots in laboratory environments to industrial applications, where heavy tasks and powerful robots are more common. In this scenario, a reliable perception of the humans involved in the process and related intentions and behaviors is fundamental. This paper presents two projects investigating the use of robots in relevant industrial scenarios, providing an overview of how industrial humanrobot collaborative tasks can be successfully addressed.

@inproceedings{lincoln48515,
       booktitle = {Ital-IA 2022},
           title = {From Human Perception and Action Recognition to Causal Understanding of Human-Robot Interaction in Industrial Environments},
          author = {Stefano Ghidoni and Matteo Terreran and Daniele Evangelista and Emanuele Menegatti and Christian Eitzinger and Enrico Villagrossi and Nicola Pedrocchi and Nicola Castaman and Marcin Malecha and Sariah Mghames and Luca Castri and Marc Hanheide and Nicola Bellotto},
            year = {2022},
             url = {https://eprints.lincoln.ac.uk/id/eprint/48515/}
}