Abstract
The reconfiguration capability given by the use of kinematic redundancy can be an alternative for enlarging the useable workspace of parallel manipulators. However, the inverse kinematic model of a kinematically redundant parallel manipulator presents an infinite number of solutions requiring redundancy resolution strategies. These decision-maker strategies are responsible for keeping the manipulator away from singular configurations, which is considered a failure. However, singular regions might be affected by uncertainties. Therefore, every possible solution for the kinematic model presents a probability of failure according to the system’s uncertainties. In this work, the probability of failure is assessed using the Monte Carlo Simulation and surrogate models. Reliable redundancy resolution strategies using these surrogate models are proposed and numerical results considering geometrical uncertainties demonstrate the proposal’s applicability.
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