Designing robust end-effector plays a crucial role, in performance of a robot workcell. Design automation of industrial grippers fingers/jaws is therefore of the highest interest in the robot industry. This paper systematically reviews the enormous studies performed in relevant research areas for finger design automation. Key processes for successfully achieving automatic finger design are identified and research contributions in each key process are critically reviewed. The proposed approaches in each key process are analyzed, verified and benchmarked. The most promising methods to accomplish finger design automation are highlighted and presented. (C) 2016 Elsevier B.V. All rights reserved.

Finger design automation for grippers is one of the areas of highest interest for robot industries. The few studies that have been carried out in the finger design automation research area are limited to objects with specific geometrical properties (e.g. polyhedral). This paper introduces the Generic Automated Finger Design (GAFD) method that contains the essential key processes for automatic design of reliable fingers. The proposed method is implemented on two geometrically complex workpieces and appropriate fingers are designed. The results are discussed in detail and benchmarked against existing approaches.

Multi-function fingers that are able to handle multiple workpieces are crucial in improvement of a robot workcell. Design automation of multi-function fingers is highly demanded by robot industries to overcome the current iterative, time consuming and complex manual design process. However, the existing approaches for the multi-function finger design automation are unable to entirely meet the robot industries need. This paper proposes a generic approach for design automation of multi-function fingers. The proposed approach completely automates the design process and requires no expert skill. In addition, this approach executes the design process much faster than the current manual process. To validate the approach, multi-function fingers are successfully designed for two case studies. Further, the results are discussed and benchmarked with existing approaches.

Design automation of industrial grippers is a hot research topic for robot industries. However, literature lacks a standard experimental method to enable researchers to validate their approaches. Thus, this paper proposes a generic experimental method to verify existing finger design approaches. The introduced method is utilized to validate the methods Generic Automated Finger Design (GAFD), Manually Designed Fingers (MDF) and the eGrip tool. Experimental results are compared and the strengths and weaknesses of each method are presented. (C) 2017 The Authors. Published by Elsevier B.V.

We present a novel technique which integratesautomatic, part centered design of customized fingertips with agrasp planning stage for arbitrary parts of an assembly process.Starting with a set of CAD models of parts in an assemblysequence, force closure grasps are generated for each part in asampling process. By employing the sampled force closure grasppositions in the second stage, the fingertip shape model isadapted to obtain form closure grasps at the specific grasplocations on the part. This approach significantly reduces theprocess time of designing fingers. Furthermore, the methodincreases the robustness of the fingers grasp for preciseassemblies. The proposed fast generic automated finger design(FGAFD) method is able to design fingers for variousgeometrically complex workpieces. The designed fingers areexperimentally verified. The results are discussed in detail andbenchmarked against existing approaches.

Finger design automation is highly demanded from robot industries to fulfill the requirements of the agile market. Nevertheless, literature lacks a promising approach to automate the design process of reliable fingers for industrial robots. Hence, this work proposes the generic optimized finger design (GOFD) method which automates the design process of single- and multi-function finger grippers. The proposed method includes an optimization algorithm to minimize the design process time. The method is utilized to generate fingers for several groups of objects. Results show that the GOFD method outperforms existing methods and is able to reduce the design time by an average of 16,600 s. While the proposed method substantially reduces the design process time of fingers, the quality of grasps is comparable to the traditional exhaustive search method. The grasp quality of GOFD deviates only 0.47% from the absolute best grasp known from the exhaustive search method in average. The designed fingers are lastly manufactured and experimentally verified.