As an emerging communication modality, brainwaves can be used to control robots for seamless assembly, especially in noisy environments where voice recognition is not reliable or when an operator is occupied with other tasks and unable to make gestures. This paper investigates human-robot collaborative assembly based on function blocks and driven by brainwaves. Using wavelet transform, brainwaves measured by EEG sensors are converted to time-frequency images and subsequently classified by a convolutional neural network (CNN) as commands to trigger a network of function blocks for assembly actions. The effectiveness of the system is experimentally validated through an engine-assembly case study.

作为一种新兴的通信方式，脑电波可用于控制机器人进行无缝组装，尤其是在语音识别不可靠或操作员忙于其他任务而无法做出手势的嘈杂环境中。本文研究了基于功能块和脑电波驱动的人机协作组装。使用小波变换，由 EEG 传感器测量的脑电波被转换为时频图像，随后由卷积神经网络 (CNN) 分类为触发功能块网络以进行组装动作的命令。该系统的有效性通过发动机装配案例研究得到了实验验证。