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.

In the near future, control systems for autonomous, intelligent manufacturing units will be required to be intelligently self-reconfiguring. Therefore, innovative development methodologies for the structured design and testing of complex control systems are mandatory. In the present work a development methodology is introduced, which is based on reference models that are compliant with emerging international standards, and exploit object-oriented concepts. By means of the proposed framework the definition of complex control systems is simplified, and the maintenance and reuse of designed control solutions is enhanced. In particular, the reconfigurability of the developed control systems is significantly improved. Furthermore, an illustrative example is presented, where the structured design of the control of an intelligent manufacturing system is discussed, describing some significant self reconfigurability functions, so highlighting the benefits of the proposed framework.