The dynamic and friction parameters of a robot are used in advanced control schemes, and their accuracy significantly affects their performance. These parameters can also be used for a realistic simulation. In principle, the numerical value of the parameters could be obtained via computer-aided design analysis but inevitable assembly and manufacturing errors exist. Direct measurement is not a realistic option because the complex nature of the system would involve an intense time-consuming effort. Alternatively, we can deduce the values of the parameters by observing the natural response of the system under appropriate experimental conditions, that is, by using identification schemes. This article presents the experimental evaluation of five identification schemes used to obtain the dynamic and friction parameters of a two-degree-of-freedom, direct-drive robot. We assume that the dynamic and friction parameters are totally unknown but, by design, the dynamic model is fully known. We consider the schemes based on the dynamic regression model, filtered-dynamic regression model, supplied-energy regression model, power regression model, and filtered-power regression model. The article presents a comparison between experimental and simulated robot responses, which enable us to verify the accuracy of each regression model.

This paper addresses the problem of impedance control of robot manipulators. An impedance controller with dynamic compensation, applied to the interaction control of robot manipulators, is presented. Previous results on motion control in task-space are extended to generate the proposed impedance controller. The approach was designed in such a way that it solves two challenges: the regulation of the interaction and a suitable path tracking. The asymptotic stability of the closed-loop system, composed by full non-linear robot dynamics and the impedance controller, is demonstrated in agreement with Lyapunov’s direct method. In addition to the theoretical background, the performance of the proposed controller is verified through simulation and experimental results obtained from the implementation of an interaction task involving a two degree-of-freedom, direct-drive robot.

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Traditional upper limb rehabilitation exercises are primarily aimed at regaining the strength or range of motion of the patients' injured area. An alternative option that has been presented in the last years is the use of haptic interfaces, which have shown their potential as tools that support rehabilitation therapies. This article presents a haptic system of rehabilitation for fine upper limb movements, whose main characteristic is that users of the system can interact in a visual and tactile fashion with virtual objects mixed with real scenarios, thereby achieving an augmented reality environment. The system was tested in two stages, both with subjects who had a degree of disability in upper limbs. The data collected were followed trajectories, follow-up errors and the muscular activity obtained by means of electromyography; the collected information enabled the analysis, in a quantitative way, of the degree of progress of the patients. In addition, the assessments made by physiotherapists were considered, concluding that the proposed system can be used as a viable complementary tool for conventional rehabilitation therapies.