BADGr-A toolbox for box-based approximation, decomposition and GRasping

Robotics and Autonomous Systems

Volumn 60, Issue 3, 2012, Pages 367-376

  Huebner, Kai ^a  

^a ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

Author keywords

3D shape approximation; Grasp database generation; Open source software; Part based grasping

Indexed keywords

3-D SHAPE; 3D POINT CLOUD; DATABASE GENERATION; HYPOTHESIS GENERATION; OPEN SOURCE SOFTWARE; PART-BASED GRASPING; SHAPE APPROXIMATION;

APPROXIMATION ALGORITHMS; OPEN SYSTEMS;

THREE DIMENSIONAL;

EID: 84856017653     PISSN: 09218890     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.robot.2011.07.021     Document Type: Article

References (47)

1. N. Krger, J. Piater, C. Geib, M. Steedman, F. Wrgtter, A. Ude, T. Asfour, R. Dillmann, Object-action complexes: grounded abstractions of sensorimotor processes, in: 4th International Conference on Cognitive Systems, 2010.
2. N. Krger, M. Lappe, and F. Wrgtter Biologically motivated multi-modal processing of visual primitives Interdisciplinary Journal of Artificial Intelligence and the Simulation of Behaviour 1 5 2004 417 427
3. L. Bodenhagen, D. Kraft, M. Popovi, E. Baeski, P.E. Hotz, N. Krger, Learning to grasp unknown objects based on 3D edge information, in: International Symposium on Computational Intelligence in Robotics and Automation, 2009, pp. 421428.
4. M. Popovi, D. Kraft, L. Bodenhagen, E. Baeski, N. Pugeault, D. Kragic, T. Asfour, and N. Krger A strategy for grasping unknown objects based on co-planarity and colour information Robotics and Autonomous Systems 58 5 2010 551 565
5. K. Huebner, S. Ruthotto, D. Kragic, Minimum volume bounding box decomposition for shape approximation in robot grasping, in: IEEE International Conference on Robotics and Automation, 2008, pp. 16281633.
6. K. Huebner, D. Kragic, Selection of robot pre-grasps using box-based shape approximation, in: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2008, pp. 17651770.
7. K. Huebner, K. Welke, M. Przybylski, N. Vahrenkamp, T. Asfour, D. Kragic, R. Dillmann, Grasping known objects with humanoid robots: a box-based approach, in: 14th International Conference on Advanced Robotics, 2009.
8. C. Borst, M. Fischer, S. Haidacher, H. Liu, G. Hirzinger, DLR hand II: experiments and experiences with an antropomorphic hand, in: IEEE International Conference on Robotics and Automation, 2003, pp. 702707.
9. A.T. Miller, S. Knoop, H.I. Christensen, P.K. Allen, Automatic grasp planning using shape primitives, in: IEEE International Conference on Robotics and Automation, 2003, pp. 18241829.
10. A. Bicchi, V. Kumar, Robotic grasping and contact: a review, in: IEEE International Conference on Robotics and Automation, 2000, pp. 348353.
11. X. Zhu, H. Ding, and J. Wang Grasp analysis and synthesis based on a new quantitative measure IEEE Transactions on Robotics and Automation 19 6 2003 942 953
12. Y.H. Liu, M. Lam, and D. Ding A complete and efficient algorithm for searching 3-D form-closure grasps in discrete domain IEEE Transactions on Robotics 20 5 2004 805 816
13. A. Morales, E. Chinellato, A.H. Fagg, and A.P. del Pobil Using experience for assessing grasp reliability International Journal of Humanoid Robotics 1 4 2004 671 691
14. N.S. Pollard Closure and quality equivalence for efficient synthesis of grasps from examples International Journal of Robotics Research 23 6 2004 595 613
15. K.B. Shimoga Robot grasp synthesis algorithms: a survey Journal of Robotics Research 15 3 1996 230 266 (Pubitemid 126547151)
16. A. Saxena, J. Driemeyer, and A.Y. Ng Robotic grasping of novel objects using vision Journal of Robotics Research 27 2 2008 157 173 (Pubitemid 351169712)
17. J. Bohg, and D. Kragic Learning grasping points with shape context Robotics and Autonomous Systems 58 4 2010 362 377
18. C. Goldfeder, P.K. Allen, C. Lackner, R. Pelossof, Grasp planning via decomposition trees, in: IEEE International Conference on Robotics and Automation, 2007, pp. 46794684. (Pubitemid 350140912)
19. F. Solina, and R. Bajcsy Recovery of parametric models from range images: the case for superquadrics with global deformations Pattern Analysis and Machine Intelligence 12 2 1990 131 147 (Pubitemid 20666139)
20. G. Biegelbauer, M. Vincze, Efficient 3D object detection by fitting superquadrics to range image data for robot's object manipulation, in: IEEE International Conference on Robotics and Automation, 2007, pp. 10861091. (Pubitemid 350140328)
21. L. Chevalier, F. Jaillet, and A. Baskurt Segmentation and superquadric modeling of 3D objects Journal of Winter School of Computer Graphics (WSCG) 2003
22. D. Katsoulas, Reliable recovery of piled box-like objects via parabolically deformable superquadrics, in: 9th IEEE International Conference on Computer Vision, vol. 2, 2003, pp. 931938.
23. E. Lopez-Damian, D. Sidobre, R. Alami, Grasp planning for non-convex objects, in: 36th International Symposium on Robotics, 2005.
24. E. Lopez-Damian, Grasp planning for object manipulation by an autonomous robot, Ph.D. Thesis, Laboratoire d'Analyse et d'Architecture des Systmes du CNRS, 2006.
25. O.J. Rubio, K. Huebner, D. Kragic, Representations for object grasping and learning from experience, in: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010, pp. 15661571.
26. N. Amenta, S. Choi, R. Kolluri, The power crust, in: 6th ACM Symposium on Solid Modeling and Applications, 2001 pp. 249260. (Pubitemid 32865691)
27. B. Rasolzadeh, M. Bjrkman, K. Huebner, and D. Kragic An active vision system for detecting, fixating and manipulating objects in real world International Journal of Robotics Research 29 23 2010 133 154
28. J. Bohg, C. Barck-Holst, K. Huebner, M. Ralph, B. Rasolzadeh, D. Song, and D. Kragic Towards grasp-oriented visual perception for humanoid robots International Journal of Humanoid Robotics 6 3 2009 387 434 (special issue on Active Vision of Humanoids)
29. S. Geidenstam, K. Huebner, D. Banksell, D. Kragic, Learning of 2D grasping strategies from box-based 3D object approximations, in: Robotics: Science and Systems, Seattle, USA, 2009, pp. 916.
30. D. Song, K. Huebner, V. Kyrki, D. Kragic, Learning task constraints for robot grasping using graphical models, in: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010, 15791586.
31. D. Song, C.H. Ek, K. Huebner, D. Kragic, Multivariate discretization for Bayesian network structure learning in robot grasping, in: IEEE International Conference on Robotics and Automation, 2011.
32. Y. Bekiroglu, K. Huebner, D. Kragic, Integrating grasp planning with online stability assessment using tactile sensing, in: IEEE International Conference on Robotics and Automation, 2011.
33. G. Barequet, and S. Har-Peled Efficiently approximating the minimum-volume bounding box of a point set in three dimensions Journal of Algorithms 38 2001 91 109 (Pubitemid 33667202)
34. G. Barequet, S. Har-Peled, A practical approach for computing the diameter of a point-set, 2000. URL:.
35. C.K. Chan, and S.T. Tan Determination of the minimum bounding box of an arbitrary solid: an iterative approach Computers & Structures 79 15 2001 1433 1449 (Pubitemid 32610536)
36. A. Morales, E. Chinellato, A.H. Fagg, A.P. del Pobil, Experimental prediction of the performance of grasp tasks from visual features, in: IEEE/RSJ International Conference on Robots and Systems, 2003, pp. 34233428.
37. L. Montesano, M. Lopes, A. Bernardino, and J. Santos-Victor Learning object affordances: from sensory-motor coordination to imitation IEEE Transactions on Robotics 24 1 2008 15 26 (Pubitemid 351411194)
38. A.T. Miller, and P.K. Allen Graspit! a versatile simulator for robotic grasping Robotics and Automation 11 4 2004 110 122 (Pubitemid 40145969)
39. OpenGRASP: a simulation toolkit for grasping and dexterous manipulation, 2011. URL: http://opengrasp.sourceforge.net/.
40. M. Novotni, R. Klein, 3D Zernike descriptors for content based shape retrieval, in: ACM Symposium on Solid and Physical Modeling, 2003, pp. 216225.
41. T. Feix, R. Pawlik, H. Schmiedmayer, J. Romero, D. Kragic, A comprehensive grasp taxonomy, robotics, science and systems conference, in: Workshop on Understanding the Human Hand for Advancing Robotic Manipulation, 2009.
42. M. Ciocarlie, C. Goldfeder, P. Allen, Dexterous grasping via eigengrasps: a low-dimensional approach to a high-complexity problem, in: RSS 2007 Manipulation Workshop, 2007.
43. C. Ferrari, J. Canny, Planning optimal grasps, in: IEEE International Conference on Robotics and Automation, 1992, pp. 22902295. (Pubitemid 23615307)
44. A. Miller, P. Allen, Examples of 3D grasp quality computation, in: IEEE International Conference on Robotics and Automation, 1999, pp. 12401246.
45. T. Asfour, K. Regenstein, P. Azad, J. Schrder, A. Bierbaum, N. Vahrenkamp, R. Dillmann, ARMAR-III: An integrated humanoid platform for sensory-motor control, in: 6th IEEE-RAS International Conference on Humanoid Robots, 2006, pp. 169175.
46. M. Przybylski, T. Asfour, R. Dillmann, Unions of balls for shape approximation in robot grasping, in: IEEE/RSJ International Conference on Robots and Systems, 2010, pp. 15921599.
47. Y. Bekiroglu, D. Kragic, V. Kyrki, Learning grasp stability with haptic data and HMMs, in: 19th IEEE International Symposium in Robot and Human Interactive Communication, 2010.