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Computation of Intersection Regions of Robotic Gripper and Deformable Object Surfaces During Grasp Planning and Simulation

Authors: Leskov A.G., Seliverstova E.V. Published: 06.12.2016
Published in issue: #6(111)/2016  
DOI: 10.18698/0236-3933-2016-6-97-114

 
Category: Informatics, Computer Engineering and Control | Chapter: Systems of Computer-Aided Design (CAD Systems)  
Keywords: grip, deformable object, simulating, intersection of polygonal models, Oriented Bounding Box, VP-tree

The study tested methods for detecting and computing the intersection regions of robotic gripper and deformable object surfaces during the grasp planning and simulation. We suggest an algorithm for detection and computation of the intersection regions comprising both broad and narrow phases. The broad phase algorithm is based on the bounding box method and is improved by introducing the original algorithm for detecting areas of potential interaction between the gripper and the object. The narrow phase algorithm is novel. It uses the nearest neighbor search methods and considers the movement direction of interacting bodies. As a result of our research, we developed a computer program and carried out experiments to analyze the efficiency of the proposed algorithms for the grasp planning with the 3-finger robotic hand Schunk SDH.

References

[1] Leskov A.G., Illarionov V.V., Kalevatykh I.A., Moroshkin S.D., Bazhinova K.V., Feoktistova E.V. Hardware-software complex for solving the task of automatic capture of the object with manipulators. Inzhenernyy zhurnal: nauka i innovatsii [Engineering Journal: Science and Innovation], 2015, iss. 1 (in Russ.). DOI: 10.18698/2308-6033-2015-1-1361 Available at: http://engjournal.ru/eng/catalog/pribor/robot/1361.html

[2] Boivin E., Sharf I., Doyon M. Optimum grasp of planar and revolute objects with gripper geometry constraints. Proc. ICRA 2004, 2004, pp. 326-332. DOI: 10.1109/R0B0T.2004.1307171

[3] Pauly M., Pai D.K., Guibas L.J. Quasi-rigid objects in contact. Proc. 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation, 2004, pp. 109-119.

[4] Ericson C. Real-time collision detection. San Francisco, Elsevier, 2005. 593 p.

[5] Gilbert E.G., Johnson D.W., Keerthi S.S. A fast procedure for computing the distance between complex objects in three-dimensional space. IEEE Journal of Robotics and Automation, 1988, vol. 4, no. 2, pp. 193-203. DOI: 10.1109/56.2083

[6] Lin M.C. Efficient collision detection for animation and robotics. PhD dissertation. University of California, Berkeley, CA, USA, 1993. 159 p.

[7] Mirtich B. V-Clip: fast and robust polyhedral collision detection. Journal ACM Transactions on Graphics, 1998, vol. 17, no. 3, pp. 177-208.

[8] Bullet Physics Library. Available at: http://bulletphysics.org/ (accessed 25.12.2015)

[9] Open Dynamics Engine. Available at: http://www.ode.org/ (accessed 25.12.2015)

[10] Preparata F.P., Shamos M.I. Computational geometry: an introduction. New York, Spinger-Verlag. 412 p. (Russ. ed.: Vychislitelnaya geometriya. Moscow, Mir Publ., 1989. 478 p.)

[11] Panigrahy R. An improved algorithm finding nearest neighbor using Kd-trees. Proc. 8th Latin American Symposium, Buzios, Brazil, 2008, vol. 26, no. 4, pp. 387-398.

[12] Maneewongvatana S., Mount D.M. An empirical study of a new approach to nearest neighbor searching. Proc. third international workshop on algorithm engineering and experimentation, Washington, DC, USA, 2001, pp. 172-187.

[13] Yianilos P.N. Data structures and algorithms for nearest neighbor search in general metric spaces. Proc. fourth annual ACM-SIAM Symposium on Discrete algorithms, Austin, TX, USA, 1993, pp. 311-321.

[14] Leskov A.G., Bazhinova K.V., Moroshkin S.D., Feoktistova E.V. Modeling of trobotic arms kinematics by means of block matrixes. Inzhenernyy zhurnal: nauka i innovatsii [Engineering Journal: Science and Innovation], 2013, iss. 9, no. 21 (in Russ.). DOI: 10.18698/2308-6033-2013-9-954 Available at: http://engjournal.ru/eng/catalog/pribor/robot/954.html