Collaborative Human and Computer Controls of Smart Machines: Literature Review

In an effort to combine machine intelligence with autonomy, Human-Machine Interface is a technology that enables direct interaction between humans and machines. One type of Human-Machine Interface is Brain-Computer Interface, where it utilizes the human brain to enable direct communication between humans and machines. The use of brain signals to control an external machine is a technique that is being investigated thoroughly in various disciplines. The main topic of this study is to investigate the need of intelligent control in dynamic environments, how human intelligence differs from machine intelligence, integration of both intelligences, utilization of brain activity to extract human intentions, hierarchical control of machine intelligence, Human-Machine Interface, and constraints of current technology. The primary findings highlights the distinctions in decision spaces between humans and machines while controlling an external device, which necessitate thorough investigation when choosing a control instrument. In addition, it highlights the restricted amount of degrees of freedom that current Brain-Computer Interfaces controllers are able to control in an external device. Hence, an extra functional module is required to convert human commands into machine-understandable high-frequency control commands in order to close these gaps. Both aspects has not been explored systematically in the literature.