A velocity estimation algorithm for legged robot

To secure the data accuracy while reducing development cost of robot, in this article, we conducted fusion estimation of the information measured by strapdown inertial navigation system and the information solved by forward kinematics using extended Kalman filter and regarding the motion parameter error was proposed as state variable. On this basis, state equation and detecting equation can be established. In addition, this article made innovative attempt to compensate the optimal estimation of motion parameter error using feedback correction method, and finally obtained stable and accurate velocity estimation of robot. Being unrestricted by the number of robot’s leg, this method is suitable for both static gait and dynamic gait, and can overcome the impact from leg slipping. As for the verification of this method, in this article, a quadruped robot was employed for motion simulation and experimental verification, and results verified the correctness and feasibility of the proposed method.