Towards Symbiotic Human-Robot Collaboration: Human Movement Intention Recognition with an EEG
Title: Towards Symbiotic Human-Robot Collaboration: Human Movement Intention Recognition with an EEG
Authors: Achim Buerkle (Intelligent Automation Centre, Loughborough University); Niels Lohse (Intelligent Automation Centre, Loughborough University); Pedro Ferreira (Intelligent Automation Centre, Loughborough University);
Year: 2019
Citation: Buerkle, A., Lohse, N., Ferreira, P., (2019). Towards Symbiotic Human-Robot Collaboration: Human Movement Intention Recognition with an EEG. UK-RAS19 Conference: “Embedded Intelligence: Enabling & Supporting RAS Technologies” Proceedings, 52-55. doi: 10.31256/UKRAS19.14
Abstract:
In order to meet the trend of customers demanding more customised and complex products, human workers and robots need to collaborate in closer proximity. Working in shared environments raises safety concerns of humans getting injured by robots. Current safety systems are mostly vision based and detect movement after it has started. This work proposes the use of an electroencephalography (EEG) which measures the brainwaves in order to detect a worker’s intention to move. This is expected to provide 0.5 seconds gain for the system to react in advance of the actual movement. In this paper the details on how EEG sensors can be integrated to detect intentions and how these can be extrapolated using machine learning techniques, are presented. The ultimate vision is to deliver an early warning system to enhance existing safety systems.