In this paper, the feedback linearization approach is used to introduce a motion controller for unicycle-type wheeled mobile robots (UWMRs). The output function is defined as a linear combination of the error state. The novel scheme is firstly tested in numerical simulation and compared with its corresponding experimental result. Three controllers are taken from the literature and compared to the proposed approach by means of experiments. The gains of the experimentally tested controllers are selected to obtain identical energy consumption. The Optitrack commercial vision system and Pioneer P3-DX UWMR are used in real-time experimental tests. In addition, two sets of experimental results for different motion tasks are provided. The results show that the proposed controller presents the best tracking accuracy.

This paper contributes by presenting a parameter identification procedure for n-degrees-of-freedom flexible joint robot manipulators. An advantage of the given procedure is the obtaining of robot parameters in a single experiment. Guidelines are provided for the computing of the joint position filtering and velocity estimation. The method relies in the filtered robot model, for which no acceleration measurements are required. The filtered model is expressed in regressor form, which allows applying a parameter identification procedure based on the least squares algorithm. In order to assess the performance of the proposed parameter identification scheme, an implementation of a least squares with forgetting factor (LSFF) parameter identification method is carried out. In order to assess the reliability of the tested identification schemes, a model-based trajectory tracking controller has been implemented twice in different conditions: one control experiment using the estimated parameters provided by the proposed scheme, and another experiment using the parameters given by the LSFF method. These real-time control experiments are compared with respect to numerical simulations using the estimated parameters for each identification method. For the proposed scheme, the comparison between experiments and numerical simulations indicates better accuracy in the torque and position prediction.