Abstract
Research focused on signals derived from the human organism is becoming increasingly popular. In this field, a special role is played by brain-computer interfaces based on brainwaves. They are becoming increasingly popular due to the downsizing of EEG signal recording devices and ever-lower set prices. Unfortunately, such systems are substantially limited in terms of the number of generated commands. This especially applies to sets that are not medical devices. This article proposes a hybrid brain-computer system based on the Steady-State Visual Evoked Potential (SSVEP), EOG, eye tracking, and force feedback system. Such an expanded system eliminates many of the particular system shortcomings and provides much better results. The first part of the paper presents information on the methods applied in the hybrid brain-computer system. The presented system was tested in terms of the ability of the operator to place the robot’s tip to a designated position. A virtual model of an industrial robot was proposed, which was used in the testing. The tests were repeated on a real-life industrial robot. Positioning accuracy of system was verified with the feedback system both enabled and disabled. The results of tests conducted both on the model and on the real object clearly demonstrate that force feedback improves the positioning accuracy of the robot’s tip when controlled by the operator. In addition, the results for the model and the real-life industrial model are very similar. In the next stage, research was carried out on the possibility of sorting items using the BCI system. The research was carried out on a model and a real robot. The results show that it is possible to sort using bio signals from the human body.
Highlights
Additional novelty was introduced with the use of force feedback on the robot’s position
Figure presents the results of virtual robot tip positioning both with enabled collected
The main goal of this work is to prove that a hybrid Brain-computer interfaces (BCIs) can provide satisfactory precision in robotic arm control to cope with difficult daily tasks
Summary
Scientific research features a trend of attempts to use it for studying the brain, and for control. Brain-computer interfaces (BCIs) are used for this purpose and are becoming increasingly popular in scientific research. These interfaces can recognize certain commands directly from the brain [1] and perform intended, predefined actions. This allows for controlling objects, such as Personal Care Robots [2]. EEG-based interfaces are quickly developing thanks to the declining prices of headsets [3]. EEG is a noninvasive method intended for registering brain activity on the skull’s surface with the use of electrodes
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