In this paper we propose the use of a dynamic model in which the effects of temperature on friction are considered to develop a virtual force sensor for industrial robot manipulators. The estimation of the inertial parameters and of the friction model are explained. The effectiveness of the virtual force sensor has been proven in a polishing task. In fact, the interaction forces between the robot and the environment has been measured both with the virtual force sensor and a common load cell. Moreover, the advantages provided by considering the temperature dependency are highlighted.

In this paper we present a new friction model for industrial robot manipulators that takes into account temperature effects. In particular, after having shown that friction might change very significantly during robot operations, two solutions based on a polynomial description of the joint friction are proposed and compared. In both cases the models proposed do not need a measurement of the joint temperature, but just of the environmental temperature, so as to be easily applied in industry. Experimental results demonstrate the effectiveness of the applied methodology.

Robot dynamics is commonly modeled as a linear function of the robot kinematic state from a set of dynamic parametersintomotortorques. Baseparameters(i.e.thesetoftheoreticallydemonstratedlinearly-independent parameters) can be reduced to a subset of “essential” parameters by eliminating those that are negligible with respect to their contribution in motor torques. However, generic trajectories, if not properly defined, couple thecontributionofsuchessentialparametersintothemotortorques,actuallyreducingtheestimationaccuracy of the dynamics parameters. The work presented here introduces an index for evaluating correlation influence among essential parameters along an executed trajectory. Such index is then exploited for an optimal search of excitatory patterns consistent with the kinematical coupling constraints. The method is experimentally compared with the results achievable by one of the most popular IRs dynamic calibration method.

This paper presents LINarm, a device for at-home robotic upper-limb neurorehabilitation. Exploiting peculiar aspects of variable-stiffness actuators, it features functionalities widely addressed by devices specifically designed for assisted rehabilitation as controlled motion, force feedback and safety, together with the low-cost requirement for a widespread installation at patients' home.

In this paper, we propose a new method, which is based on an iterative-learning-control (ILC) algorithm, for the contour tracking of an object of unknown shape performed by an industrial robot manipulator. In particular, we consider (both implicit and explicit) hybrid force/velocity control whose performance is improved by repeating the task. Here, a time-based reference signal is not present, and therefore, a new approach has been developed, which is different from the typical applications of ILC. Experimental results show the effectiveness of the technique.

The paper investigates the decoupling of an explicit hybrid force/velocity control of robot manipulators employed in the contour tracking task of objects of unknown shape taking into account the elastic model of the contact and of the robot. The proposed controller allows the achievement of the decoupling of the normal force and tangential velocity control loops and can be expressed as a multi-input multi-output (MIMO) time-varying proportional-integral-derivative (PID) controller. Experimental results demonstrate the effectiveness of the method.

In this paper we propose a new method, based on an iterative learning control (ILC) algorithm, for the contour tracking of a planar object of unknown shape performed by an industrial SCARA robot manipulator. In particular, we adopt a hybrid force/velocity controller whose performance is improved by repeating the task. Differently from the typical applications of ILC, here a reference position signal is not present and therefore a new approach has been developed. Experimental results show the effectiveness of the technique

This paper deals with the experimental charactherization of an hybrid force/velocity controller for contour tracking tasks of objects with unknown shape performed by industrial robot manipulators. In particular, we address the problem of the presence of elasticities in joint transmissions, and we show that this can cause the occurrence of large force oscillations depending on the robot configuration. We also show that to compensate for them it is necessary to employ an additional normal velocity feedback loop. Experimental results have been obtained with a two degrees-of-freedom SCARA robot.

In this paper we experimentally analyze the performances of an hybrid force/velocity controller for the automatic edge following of 2D unknown planar contours performed by a robot manipulator. In this work we show that joint friction effects have to be taken into account in the controller design in order to achieve reasonable performances in terms of normal force and tangential velocities errors. For this reason we compare two model-based methods for coping with friction: a static one based on a previously identified model and an adaptive one recursively updating joint friction parameters. The proposed controllers are compared through an extensive experimental activity on a 2-DOF SCARA robot tracking an high stiffness aluminium-bar over a wide range of operative conditions.