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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. [ABSTRACT FROM AUTHOR]

This paper deals with the implementation of a hybrid force/velocity controller for the automatic edge following of two-dimensional unknown planar contours performed by an industrial robot manipulator. In particular, the authors address the problem of compensating the joint friction effects that have to be taken into account in the controller design in order to achieve a reasonable performance with regards to normal force and tangential velocity errors. For that reason, two model-based friction-compensation methods are compared: a static method, based on a previously identified model, and an adaptive method, where joint friction parameters are recursively updated. By means of an extensive experimental activity, it is shown that, in spite of its simplicity and despite the friction effects changing in time during the robot operations, the devised adaptive procedure obtains a high performance in different operating conditions. [ABSTRACT FROM AUTHOR]