A Multi-Modal Robotic Gripper with a Reconfigurable Base: Improving Dexterous Manipulation without Compromising Grasping Efficiency

Design optimization can lead to the development of robotic end-effectors with optimal grasping and dexterous, in-hand manipulation capabilities. In particular, the finger link dimensions have been identified as one of the primary design parameters that affects the performance of a robotic gripper. The ability of a gripper to manipulate objects is mainly attributed to the interaction between a set of coordinated fingers. This coordination is primarily affected by the inter-finger distance. This paper presents a framework for finding an appropriate distance between the finger bases of a two-fingered robotic gripper so as to increase the dexterous manipulation workspace for a range of object sizes. To do that, a parallel multi-start search algorithm is employed to solve a multiparametric optimization problem. The results demonstrate that different distances lead to completely different workspace shapes and that the ratio defined by the area of the optimized workspace (nominator) and the union of all workspaces (denominator) is always significantly less than 1. This means that the area of the union of all workspaces is always larger than the area of the "optimized" workspace. Based on these results a multi-modal robotic gripper with movable finger bases was developed. The proposed gripper can vary the distance between the finger bases online and it offers an increased dexterous manipulation workspace without sacrificing grasping performance.