Physically feasible dynamic parameter identification of the 7-DOF WAM robot

This paper presents the dynamic parameter identification of the 7-DOF WAM™Arm using a novel physically consistent regression technique. Due to model and data errors, physically impossible parameters can arise with classical estimations methods. Such infeasible estimations cannot be used in robot control or simulation. This paper proposes a semidefinite programming (SDP) reformulation of the classical ordinary least squares method. This enables the inclusion of constraints guaranteeing physically feasible solutions only. The SDP method efficiently finds the feasible solution with the lowest regression error. Regression data processing issues related to the WAM robot are also addressed.