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Offline procedures for estimating parameters of robot dynamics arepractically based on the parameterized inverse dynamic model. In this paper, wepresent a novel approach to parameter estimation of robot dynamics whichremoves the necessity of parameterization (i.e. finding the minimum number ofparameters from which the dynamics can be calculated through a linear modelwith respect to these parameters). This offline approach is based on a simpleand powerful swarm intelligence tool: the particle swarm optimization (PSO). Inthis paper, we discuss and validate the method through simulated experiments.In Part Two we analyze our method in terms of robustness and compare it torobust analytical methods of estimation.

Use of PSO in Parameter Estimation of Robot Dynamics; Part One: No Need for Parameterization