Brain Computer Interfaces for Supervisory Controls of Unmanned Aerial Vehicles *

To deal with changes and uncertainties in controlling a Unmanned Aerial Vehicle (UAV) reliably, a new platform is proposed to synergize human and machine intelligence, and it is based on a new Brain Computer Interface (BCI) to (1) quantify human’s affections in arbitrating human and machine intelligence and alleviating adverse effects by human’s mistakes, (2) fuse human and machine’s control commands in different frequencies seamlessly and generate control commands at motor levels for real-time performance. In this paper, existing works on BCIs are discussed to identify the limitations of traditional Human-Machine Interactions (HMIs), a new framework of HMIs is proposed for a supervisory control of UAV; in particular, it is equipped with an arbitrating mechanism to optimize the shared control of UAVs based on quantified states of human’ affection. It is expected to improve adaptability, agility, and reliability, responsiveness, and resilience of UAVs. This is an ongoing project, and the development platform for the feasibility study of the proposed method is introduced as our plan for future work.