A velocity estimation algorithm for legged robot

Abstract

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.

A Strong Tracking Mixed-Degree Cubature Kalman Filter Method and Its Application in a Quadruped Robot

“…where the connecting rod angles are transverse joint angle 1 θ , hip joint angle 2 θ , knee joint angle 0 Connecting rod coordinate system of right front leg of quadruped robot[20].…”

Robust inverse dynamics by evaluating Newton–Euler equations with respect to a moving reference and measuring angular acceleration

“…For the numerical derivatives of the linear and angular momentum, the knowledge of the linear velocity of at least one segment is required. Wang et al (2017) or Kimura et al (2018) show approaches to estimate the linear velocity vector. As mentioned before, mostly the reference point for the balance of angular momentum is referenced to a fixed point in the inertial frame (WF) or the immaterial COM.…”