A robot control method, a legged robot using the same, and a computer-readable storage medium are provided. The method includes: obtaining a motion parameter of a driving mechanism of a target part of the robot; and obtaining an end pose of the target part by processing the motion parameter of the driving mechanism according to a preset forward kinematics solving model, where the forward kinematics solving model is a neural network model trained by a preset training sample set constructed according to a preset inverse kinematics function relationship. In this manner, a complex forward kinematics solving process can be transformed into a relatively simple inverse kinematics solving process and neural network model processing process, which reduces the computational complexity, shortens the computational time, thereby meeting the demand for real-time control of the robot.