The invention relates to a
humanoid robot whole body motion control method and
system based on guide learning and remapping data. According to the method, guide learning is adopted as a
motion control algorithm framework of the
humanoid robot; the method comprises the following steps: firstly, acquiring
human body weight mapping data, and performing coordinate transformation on the
human body weight mapping data to serve as a feedforward action in guide learning; constructing a neural network, inputting an observation vector of the
robot into the neural network, carrying out
reinforcement learning on the neural network, outputting rotation angle data, needing to be finely adjusted, of each joint of the
robot, carrying out
exponential smoothing processing on the rotation angle data, and outputting a smoothed
signal as a feedback
signal; and the feedforward action and the feedback
signal are combined through PD control to generate a final rotation angle required by each joint of the
robot, and then the rotation angle is converted into an output torque of a motor and output, so that whole-body
motion control of the
humanoid robot is completed. Compared with the prior art, the method has the advantages that the action accuracy and the real-time fine adjustment requirement are both considered, and the control robustness is high.