Parallel manipulators offer much higher rigidity and smaller mobile mass than their serial counterparts, thus allowing much faster and more precise manipulations. The main disadvantage of parallel robots is their small workspace in comparison to serial arms of similar size. Furthermore, the manipulability of parallel robots is often poor in some regions of the (already small) workspace. Another problematic issue is effective modeling of parallel robot dynamics, often needed for control algorithms. Dynamic algorithms developed for serial robots or general closed-loop mechanisms cannot be easily applied to parallel robots when the objective is real-time, dynamicmodelbased control. Therefore, in this work we investigate how to design parallel manipulators so that their workspace size and manipulability are maximized, and how to model parallel robot dynamics effectively. We develop a new performance index that combines measures of manipulability and workspace size, and a kinematic optimization process yieldin
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