  Off-line robot dynamic identification methods are mostly based on the use of
the inverse dynamic model, which is linear with respect to the dynamic
parameters. This model is sampled while the robot is tracking reference
trajectories that excite the system dynamics. This allows using linear
least-squares techniques to estimate the parameters. The efficiency of this
method has been proved through the experimental identification of many
prototypes and industrial robots. However, this method requires the joint
force/torque and position measurements and the estimate of the joint velocity
and acceleration, through the bandpass filtering of the joint position at high
sampling rates. The proposed new method requires only the joint force/torque
measurement. It is a closed-loop output error method where the usual joint
position output is replaced by the joint force/torque. It is based on a
closed-loop simulation of the robot using the direct dynamic model, the same
structure of the control law, and the same reference trajectory for both the
actual and the simulated robot. The optimal parameters minimize the 2-norm of
the error between the actual force/torque and the simulated force/torque. This
is a non-linear least-squares problem which is dramatically simplified using
the inverse dynamic model to obtain an analytical expression of the simulated
force/torque, linear in the parameters. A validation experiment on a 2
degree-of-freedom direct drive robot shows that the new method is efficient.
