An analysis of grasp quality measures for the application of sheet metal parts grasping

Acquiring a qualitative force-closure grasp requires the determination of feasible contact points on the object based on a defined criterion. The determination must be fast in order to implement feasible synthesis algorithms. Moreover, grasping of sheet metal parts has further requirements derived from its geometry and clamping tools. This paper presents a grasp quality analysis for the application of sheet metal parts. Moreover, a novel grasp quality measure approach is proposed based on standard deviation computation of the contact’s coordinates. The proposed measure is frame invariant, simple to implement, and has low computational complexity. A comparative analysis over other measures is presented. Further, a stress analysis was performed to show that the proposed criterion yields low stress on the sheet metal part compared to other criteria. Simulations show advantage to grasp synthesis with the proposed quality measure.

[1]  Máximo A. Roa,et al.  Geometrical approach for grasp synthesis on discretized 3d objects , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  Richard M. Murray,et al.  A Mathematical Introduction to Robotic Manipulation , 1994 .

[3]  Yizhar Or,et al.  Computation and Graphical Characterization of Robust Multiple-Contact Postures in Two-Dimensional Gravitational Environments , 2006, Int. J. Robotics Res..

[4]  Robert B. Fisher,et al.  Ranking planar grasp configurations for a three-finger hand , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[5]  John F. Canny,et al.  Easily computable optimum grasps in 2-D and 3-D , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[6]  Joel W. Burdick,et al.  A stiffness-based quality measure for compliant grasps and fixtures , 2000, IEEE Trans. Robotics Autom..

[7]  B. Faverjon,et al.  On computing three-finger force-closure grasps of polygonal objects , 1991 .

[8]  Tadej Bajd,et al.  Estimation of hand preshaping during human grasping. , 2005, Medical engineering & physics.

[9]  G. W. Stewart,et al.  On the Early History of the Singular Value Decomposition , 1993, SIAM Rev..

[10]  Ying Li,et al.  Data-Driven Grasp Synthesis Using Shape Matching and Task-Based Pruning , 2007, IEEE Transactions on Visualization and Computer Graphics.

[11]  K. Pearson.  VII. Note on regression and inheritance in the case of two parents , 1895, Proceedings of the Royal Society of London.

[12]  Jingxia Yuan,et al.  Deformable Sheet Metal Fixturing: Principles, Algorithms, and Simulations , 1996 .

[13]  Micha Sharir,et al.  On the existence and synthesis of multifinger positive grips , 2015, Algorithmica.

[14]  Máximo A. Roa,et al.  Grasp quality measures: review and performance , 2014, Autonomous Robots.

[15]  Avishai Sintov,et al.  OCOG: A common grasp computation algorithm for a set of planar objects , 2014 .

[16]  Danica Kragic,et al.  Classical grasp quality evaluation: New algorithms and theory , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[17]  Ian T. Jolliffe,et al.  Principal Component Analysis , 2002, International Encyclopedia of Statistical Science.

[18]  Yunhui Liu.  Computing n-Finger Form-Closure Grasps on Polygonal Objects , 2000, Int. J. Robotics Res..

[19]  Thanathorn Phoka,et al.  A Heuristic Approach for Computing Frictionless Force-Closure Grasps of 2D Objects from Contact Point Set , 2006, 2006 IEEE Conference on Robotics, Automation and Mechatronics.

[20]  William L. Cleghorn,et al.  Flexible fixture design with applications to assembly of sheet metal automotive body parts , 2006 .

[21]  Michael Ian Shamos,et al.  Computational geometry: an introduction , 1985 .

[22]  Dariusz Ceglarek,et al.  Impact of fixture design on sheet metal assembly variation , 2004 .

[23]  Máximo A. Roa,et al.  Regrasp planning in the grasp space using independent regions , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[24]  Vijay Kumar,et al.  Planar, bimanual, whole-arm grasping , 2012, 2012 IEEE International Conference on Robotics and Automation.

[25]  Gary M. Bone,et al.  Unilateral fixtures for sheet-metal parts with holes , 2004, IEEE Transactions on Automation Science and Engineering.

[26]  James K. Mills,et al.  Three-dimensional localization of thin-walled sheet metal parts for robotic assembly , 2002, J. Field Robotics.

[27]  David G. Kirkpatrick,et al.  Quantitative Steinitz's theorems with applications to multifingered grasping , 1990, STOC '90.

[28]  Byoung-Ho Kim,et al.  Non-dimensionalized performance indices based optimal grasping for multi-fingered hands , 2004 .

[29]  Gerd Hirzinger,et al.  A fast and robust grasp planner for arbitrary 3D objects , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[30]  Peter K. Allen,et al.  Examples of 3D grasp quality computations , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[31]  Anis Sahbani,et al.  An overview of 3D object grasp synthesis algorithms , 2012, Robotics Auton. Syst..

[32]  John F. Canny,et al.  Planning optimal grasps , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[33]  Yizhar Or,et al.  Analytic Characterization of a Class of Three-contact Frictional Equilibrium Postures in Three-dimensional Gravitational Environments , 2010, Int. J. Robotics Res..