In the recent years, the industry has seen the introduction of the collaborative robots (or 'cobots'), designed to interact with human workers in a shared environment. However, the involvement of the cobots in industrial applications is still strongly influenced by the strategies for non-collaborative robotic cells. The researchers are working frantically to find solutions to improve the interactions between the cobot and the operator, simplifying the communication and the programming work. This paper proposes a task-based algorithm which allows a fluid interaction, via biosignals of a Brain Compute Interface (BCI), as an enabling strategy of the collaborative workstations. The goal is to provide an implementation method of the BCI devices for industrial applications in order to make the cobots easy to use and interact with. The proposed solution is tested on an experimental setup which uses the Steady-State Visual Evoked Potential (SSVEP) response signal to drive machine commands to a collaborative robotic arm.

Brain computer interface for human-cobot interaction in industrial applications

Dmytriyev Y.;Zaki A. M. A.;Carnevale M.;Insero F.;Giberti H.
2021-01-01

Abstract

In the recent years, the industry has seen the introduction of the collaborative robots (or 'cobots'), designed to interact with human workers in a shared environment. However, the involvement of the cobots in industrial applications is still strongly influenced by the strategies for non-collaborative robotic cells. The researchers are working frantically to find solutions to improve the interactions between the cobot and the operator, simplifying the communication and the programming work. This paper proposes a task-based algorithm which allows a fluid interaction, via biosignals of a Brain Compute Interface (BCI), as an enabling strategy of the collaborative workstations. The goal is to provide an implementation method of the BCI devices for industrial applications in order to make the cobots easy to use and interact with. The proposed solution is tested on an experimental setup which uses the Steady-State Visual Evoked Potential (SSVEP) response signal to drive machine commands to a collaborative robotic arm.
2021
978-1-6654-4058-5
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1450675
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