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Currently there still remains a critical need of human involvements for multi-robot system (MRS) to successfully perform their missions in real-world applications, and the hand-controller has been commonly used for the operator to input MRS control commands. However, in more challenging scenarios involving concurrent MRS control and system monitoring tasks, where the operator&#x2019;s both hands are busy, the hand-controller alone is inadequate for effective human-MRS interaction. To this end, our study takes a first step toward a multimodal interface by extending the hand-controller with a hands-free input based on gaze and brain-computer interface (BCI), i.e., a hybrid gaze-BCI. Specifically, the velocity control function is still designated to the hand-controller that excels at inputting continuous velocity commands for MRS, while the formation control function is realized with a more intuitive hybrid gaze-BCI, rather than with the hand-controller via a less natural mapping. In a dual-task experimental paradigm that simulated the hands-occupied manipulation condition in real-world applications, operators achieved improved performance for controlling simulated MRS (average formation inputting accuracy increases 3&#x0025;, average finishing time decreases 5 s), reduced cognitive load (average reaction time for secondary task decreases 0.32 s) and perceived workload (average rating score decreases 15.84) with the hand-controller extended by the hybrid gaze-BCI, over those with the hand-controller alone. These findings reveal the potential of the hands-free hybrid gaze-BCI to extend the traditional manual MRS input devices for creating a more operator-friendly interface, in challenging hands-occupied dual-tasking scenarios.

Extended Control With Hybrid Gaze-BCI for Multi-Robot System Under Hands-Occupied Dual-Tasking