At the 2026 World Artificial Intelligence Conference held today, BrainCo officially launched the world’s first integrated, graphical, one-stop AI research platform for brain-controlled robot research and development – the BrainCo Brain-Controlled Robot Training Platform .
According to official information obtained by Tech free press, this platform integrates EEG acquisition, experimental paradigms, neural decoding, control mapping, and robot execution into a unified software process, lowering the system construction threshold for the research on the fusion of brain-computer interfaces and robots. Even researchers without a background in brain-computer interfaces can unlock the ability to control robots with their “thoughts” within 10 minutes.
1. Working principle of brain-controlled robot training platform
When a person intends to perform an action, the brain emits weak electroencephalogram (EEG) signals. The working principle of brain-controlled robots is to collect EEG signals related to a specific task through sensors, use algorithms to identify intention-related patterns, and then convert the identification results into executable instructions for the robot’s control system, driving the robot to complete the corresponding action. Simply put, it establishes an information pathway between the human brain and the robot, allowing human intentions to be directly translated into machine actions, without relying on traditional interaction methods such as buttons, remote controls, gamepads, and voice commands.
2. Brain-controlled robot AI research platform, realizing the integration of complex R&D processes.
The brain-controlled robot AI research platform recently released by BrainPower Technology integrates experimental processes that previously required multidisciplinary backgrounds and lengthy cycles into a standardized platform. The platform consists of three parts: an EEG sensing system, a software platform, and a robot actuator. The EEG sensing system is responsible for acquiring EEG signals, is compatible with multiple electrode types, supports multi-channel, high-sampling-rate data acquisition, and can transmit data wirelessly in real time.
The software platform handles the core tasks of signal processing and robot control, and incorporates a brain-computer interface experimental paradigm and neural decoding algorithms. Researchers don’t need to build the underlying algorithms from scratch; they only need to configure the software platform to achieve the entire process from signal acquisition to control output, which explains its “10-minute learning curve.” The robot actuator currently supports integration with various third-party robots and devices, including humanoid robots, robotic arms, and robot dogs. The platform is also continuously adding new robot models, allowing researchers to choose the appropriate robot for their experiments based on their research interests.
