Backward sequential approach for dynamic parameter identification of robot manipulators

This article proposes a sequential optimization approach to efficiently identify non-minimal dynamic parameters of robot manipulators, possibly having large degrees of freedom. A back-substitution-based parameter identification from the last link to inward links is enabled due to the block upper triangular form of inherent regressor matrix. Starting with the dynamic model using the non-minimal parameters, we derive a generic compact formulation for the linear regression equation. We then establish a sequential optimization procedure taking into account physical feasibility of parameters. Numerical case examples demonstrate the validity of the proposed approach.