Enhancing the useful workspace of a reconfigurable parallel manipulator by grasp point optimization

Reconfigurable parallel manipulators combine the properties of parallel manipulators with high flexibility. However, the workspace of parallel manipulators is, compared to serial manipulators, relatively small and hence the optimization of the useful workspace is an important design factor. Different efficient algorithms for calculating the workspace for parallel manipulators have been developed, but they need to be adapted to reconfigurable systems with additional parameters. These variables for those systems are the parameters of the reconfiguration, e.g. the grasping points. This paper presents a method to obtain the grasping point combinations of a parallel reconfigurable manipulator that leads to a useful workspace containing the largest geometric object. The largest geometric object inside the useful workspace describes its regularity and represents a useful evaluation criterion. The method is introduced for a general reconfigurable parallel manipulator and then studied for the particular case of the PARAGRIP reconfigurable parallel manipulator. The workspace is obtained by applying a combined geometrical and discretization method. To reduce the possible grasping point combinations and thereby reduce computational cost, we apply the special requirements that the grasping point combinations must fulfil. By solving the inverse kinematic problem for each combination the useful workspace is calculated. HighlightsWe present a method for parallel reconfigurable manipulators.We get the grasping point combinations with the biggest free-singularity workspace.We obtain the combinations that lead to the biggest sphere in the useful workspace.We introduce the method for a general case.We focus on the parallel reconfigurable manipulator PARAGRIP case.