Abstract
In this paper, authors present a novel architecture for controlling an industrial robot via Brain Computer Interface. The robot used is a Series 2000 KR 210-2. The robotic arm was fitted with DI drawing devices that clamp, hold and manipulate various artistic media like brushes, pencils, pens. User selected a high-level task, for instance a shape or movement, using a human machine interface and the translation in robot movement was entirely demanded to the Robot Control Architecture defining a plan to accomplish user's task. The architecture was composed by a Human Machine Interface based on P300 Brain Computer Interface and a robotic architecture composed by a deliberative layer and a reactive layer to translate user's high-level command in a stream of movement for robots joints. To create a real-case scenario, the architecture was presented at Ars Electronica Festival, where the A3-K3 architecture has been used for painting. Visitors completed a survey to address 4 self-assessed different dimensions related to human-robot interaction: the technology knowledge, the personal attitude, the innovativeness and the satisfaction. The obtained results have led to further exploring the border of human-robot interaction, highlighting the possibilities of human expression in the interaction process with a machine to create art.
Highlights
It is composed by two main modules, the Human Machine Interface (HMI) and the Robot Control Architecture (RCA)
To evaluate the general attitude toward the A3-K3 architecture and to understand if people perceived such concept acceptable or not, authors prepared a questionnaire which has been submitted to Ars Electronica Festival visitors2 to assess 4 principal dimensions: technology knowledge, attitude, interaction and satisfaction
The architecture has been designed to be modular with two main systems, the Human Machine Interface and the Robot Control Architecture
Summary
The Brain Computer Interface (BCI) is a direct method of communication between a human brain and a computer. It measures brain activity associated with the user’s intention and translates the recorded brain activity into corresponding control signals for BCI applications (Graimann et al, 2010). Using BCIs by people with severe paralysis (e.g., Amyotrophic lateral sclerosis (ALS) neurological disease) for communication controlling external devices (Spataro et al, 2017) and for extending the physical presence (Chella et al, 2009), especially in clinical applications, is well known. Münßinger et al (2010) evaluated the results of a painting application based on brain computer interface on healthy subject and ALS patient.
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