Demonstrates multi-agent control through EEG signals in patients with motor impairments, suggesting improved navigation efficacy.
This paper presents a cognitive architecture for controlling robotic agents via a brain–computer interface (BCI). Aimed at patients with motor and speech impairments, the system translates high-level user intentions, decoded from EEG (Electroencephalography) signals, into conflict-free navigation for a group of wheelchairs. Experiments confirm the feasibility of multi-agent control based on a single global command, without requiring direct human intervention.
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Akopyan et al. (2026) studied this question.
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