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.

使用运动学冗余提供的重新配置能力可以成为扩大并联机械手可用工作空间的替代方案。然而，运动学冗余并联机械手的逆运动学模型提出了无数需要冗余解决策略的解决方案。这些决策者策略负责使操纵器远离单一配置，这被认为是失败的。然而，单一区域可能会受到不确定性的影响。因此，根据系统的不确定性，运动学模型的每个可能的解决方案都呈现出故障的概率。在这项工作中，使用蒙特卡罗模拟和代理模型评估故障概率。