Inertia parameter identification of biped robot using ZMP feedback

Abstract:

The existing parameter identification method of biped robot that uses the joint torque has low identification precision. The identification method based on full contact force and motion capture data requires additional equipment, which limits the application in a large range. Regarding this problem, a method for inertial parameter identification of biped robot based on ZMP data is proposed. The objective function is defined as the position deviation of the theoretical ZMP and the actual ZMP. The range of the parameters and the total weight of robot are considered as two constraint conditions. Then the optimization model of inertial parameter identification of biped robot is established, which only needs sample data acquired from the robot itself. Because the built model cannot be split into linear form, the gradient vector and Hessian matrix of the objective function are derived with respect to the parameter vector. Also, the optimization algorithm is given based on steepest descent method and Newton method. Using the biped part of the GoRoBoT-II robot, the inertial parameter identification experiment of the leg links is carried out. The proposed method is compared with the traditional identification method based on joint torque. It is found that the result of the proposed ZMP-based identification method is closer to the nominal value of the parameters obtained by 3D geometric modeling. Also, the deviation between theoretical ZMP and actual ZMP is 4.6 mm, which is smaller than the deviation (12.4 mm) of traditional method, indicating that the proposed ZMP-based parameter identification method can obtain better results than traditional methods.