Abstract
In the last years, the development of robots for assisting and collaborating with people has experienced a large growth. Applications for assistive robots include hospital service robots, factory intelligent assistants and personal homecare robots. Working in shared environments with human beings, these robots require effective ways to achieve an increasing human-robot cooperation. This work presents a possible approach for performing human-robot cooperation, namely recognition of a user selected object by means of Brain Computer Interface (BCI), followed by pick and place via a robotic arm. The object selection is achieved introducing a BCI that allows the user, after a training phase, to choose one among six different objects of common diffusion. The selection is achieved by interpreting the P300 signals generated in the brain, when the image of the object, desidered by the user, appears on a computer screen as a visual stimulus. The robot then recognizes, through a classifier, the selected object among others within its workspace, and inscribes it in a rectangle shape. Finally, the robot arm is moved in correspondence to the object position, the gripper is rotated according to the object orientation and the object grasped and moved into a different position on a desk in front of the robot. This system could support people with limited motor skills or paralysis, playing an important role in structured assistive environments in a near future.
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Acknowledgements
Authors would like to thank Simone Hanisch, Davide Centioni, Massimo Martini and Diego Retaggi, who contributed to some of the algorithms described in the paper.
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Foresi, G. et al. (2019). Human-Robot Cooperation via Brain Computer Interface in Assistive Scenario. In: Casiddu, N., Porfirione, C., Monteriù, A., Cavallo, F. (eds) Ambient Assisted Living. ForItAAL 2017. Lecture Notes in Electrical Engineering, vol 540. Springer, Cham. https://doi.org/10.1007/978-3-030-04672-9_8
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DOI: https://doi.org/10.1007/978-3-030-04672-9_8
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