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In an era where human–machine interaction is at the forefront of technological advancement, the search for a seamless and responsive interface between human cognition and robotic control is supreme. This paper delves into the creation of an IoT-enabled mind-controlled robot, an innovation poised to redefine the boundaries of human–robot collaboration. The challenge addressed here is the establishment of Brain-Computer Interface (BCI) which is real-time, having precise control over a robotic platform using EEG-based brain signals. Leveraging NodeMcu devices and wireless communication, this study pioneers a Server-Client Model for facilitating uninterrupted communication between the user and the robot. Within this framework, the user interface NodeMcu captures EEG signals via specialized sensors, while signal processing algorithms extract meaningful patterns. These patterns are mapped to predefined commands, which, when transmitted to the robotic platform NodeMcu, are transformed into motor control signals, driving the robot's movements. This dynamic interaction not only showcases the potential of mind-controlled robotics but also opens new horizons for intuitive and efficient human–robot collaboration.

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Neuro-Cybernetics: Enabling Human–Machine Interaction Through Brain Signals

  • 会议论文

  • 发表日期：

    2025年

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  • Mukund Kulkarni,
  • Tanmay Lautawar,
  • Kunal Bhalgat,
  • Kuntesh Nandankar,
  • Yogita Lad,
  • Niranjan Langade

摘要

In an era where human–machine interaction is at the forefront of technological advancement, the search for a seamless and responsive interface between human cognition and robotic control is supreme. This paper delves into the creation of an IoT-enabled mind-controlled robot, an innovation poised to redefine the boundaries of human–robot collaboration. The challenge addressed here is the establishment of Brain-Computer Interface (BCI) which is real-time, having precise control over a robotic platform using EEG-based brain signals. Leveraging NodeMcu devices and wireless communication, this study pioneers a Server-Client Model for facilitating uninterrupted communication between the user and the robot. Within this framework, the user interface NodeMcu captures EEG signals via specialized sensors, while signal processing algorithms extract meaningful patterns. These patterns are mapped to predefined commands, which, when transmitted to the robotic platform NodeMcu, are transformed into motor control signals, driving the robot's movements. This dynamic interaction not only showcases the potential of mind-controlled robotics but also opens new horizons for intuitive and efficient human–robot collaboration.