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The ability to grasp large objects with both hands enables bimanual robot systems to fully employ their capabilities in human-centered environments. Hence, algorithms are needed to precompute bimanual grasping configurations that can be used online to efficiently create whole body grasps. In this work we present a bimanual grasp planner that can be used to build a set of grasps together with manipulability information for a given object. For efficient grasp planning precomputed reachability information and a beneficial object representation, based on medial axis descriptions, are used. Since bimanual grasps may suffer from low manipulability, caused by a closed kinematic chain, we show how the manipulability of a bimanual grasp can be used as a quality measure. Therefore, manipulability clusters are introduced as an efficient way to approximatively describe the manipulability of a given bimanual grasp. The proposed approach is evaluated with a reference implementation, based on Simox 1, for the humanoid robot ARMAR-III 2. Since the presented algorithms are robot-independent, there are no limitations for using this planner on other robot systems.
Vahrenkamp et al. (Sat,) studied this question.