In this paper some simple linear and nonlinear controllers for two different multifingered grippers-the Karlsruhe Dexterous Hand, and the Salisbury Hand developed at INRIA-are discussed. Mainly the nonlinear friction, the impact problem and other plant uncertainties require a special kind of control and tuning of the controller. An adaptive fuzzy controller is presented to overcome the time consuming process of fine-tuning of the membership functions. Finally, the used service- and object-oriented approach to ease and accelerate the control system design and software implementation process is outlined.

Controlling multifingered robot hands makes high demands on the control algorithms and the speed of the control computer. The nonlinear friction, the impact problem and other plant uncertainties require a special kind of control and tuning of the controller. Some simple linear and nonlinear controllers for the Karlsruhe Dexterous Hand are presented and the results and advantages of the controllers are shown. Also, a new adaptive fuzzy controller is presented to overcome the time consuming process of fine-tuning the membership functions. Finally, a short glance at the hardware platform is taken in order to show the control system architecture.

Performing fine manipulations with multifingered robot hands makes high demands on the control algorithms and the speed of the control computer. Mainly nonlinear friction problems and plant uncertainties require intensive fine-tuning of a controller. This paper gives insight into the frictional behaviour of geared finger links. The behaviour has been approximated by a friction model. Considering the estimated system parameters two kinds of controllers are developed: a simple PD controller with switchable I-part and a PD-controller with a fuzzy friction compensation working in parallel. The results of both controllers are presented and compared in this paper.