In
this paper, we propose a motion planning system for bin picking using 3-D point
cloud. The situation that the objects are put miscellaneously like the inside
in a house is assumed. In the home, the equipment which makes an object stand
in line doesn’t exist. Therefore the motion planning system which considered a
collision problem becomes important. In this paper, Information on the objects is
measured by a laser range finder (LRF). The information is used as 3-D point
cloud, and the objects are recognized by model-base. We propose search method
of a grasping point for two-fingered robotic hand, and propose search method of
a path to approach the grasping point without colliding with other objects.
References
[1]
Kawata, H., Ohya, A., Yuta, S., Santosh, W. and Mori, T. (2005) Development of Ultra-Small Lightweight Optical Range Sensor System. Proceedings of IEEE International Conference on Intelligent Robots and Systems, 2-6 August 2005, 1078-1083. http://dx.doi.org/10.1109/iros.2005.1545476
[2]
Johnson, A.E. and Hebert, M. (1999) Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21, 433-449. http://dx.doi.org/10.1109/34.765655
[3]
Mian, A.S., Bennamoun, M. and Owens, R.A. (2006) A Novel Representation and Feature Matching Algorithm for Automatic Pairwise Registration of Range Images. International Journal of Computer Vision, 66, 19-40. http://dx.doi.org/10.1007/s11263-005-3221-0
[4]
Hetzel, G., Leibe, B., Levi, P. and Schiele, B. (2001) 3D Object Recognition from Range Images Using Local Feature Histograms. IEEE Computer Vision and Pattern Recognition, 2, 394-399.
[5]
Gumhold, S., Wang, X. and Macleod, R. (2001) Feature Extraction from Point Clouds. Proceeding of the 10 International Meshing Roundtable, Sandia national Laboratories, 293-305.
[6]
Kodani, K., Manabe, T. and Taniguchi, T. (2003) Surface Generation from Point Cloud on Surface of 3D Domain. Proceedings of Computational Engineering Conference, 8, 837-840
[7]
Xu, F. and Hagiwara, I. (2007) Developing of Registration System for Range Scan Data. Proceedings of the 26th Japan Simulation Conference, 15-118.
[8]
Johnson, A.E. and Kang, S.B. (1999) Registration and Integration of Textured 3-D Data. Image and Vision Computing, 17, 135-147. http://dx.doi.org/10.1016/S0262-8856(98)00117-6
[9]
Akca, D. (2007) Matching of 3D Surfaces and Their Intensities. ISPRS Journal of Photogrammetry and Remote Sensing, 62, 112-121. http://dx.doi.org/10.1016/j.isprsjprs.2006.06.001
[10]
Tombari, F., Salti, S. and Stefano, L.D. (2010) Unique Signatures of Histograms for Local Surface Description. Computer Vision - ECCV, 356-369. http://dx.doi.org/10.1007/978-3-642-15558-1_26
[11]
Tombari, F. and Stefano, L.D. (2012) Hough Voting for 3D Object Recognition under Occlusion and Clutter. IPSJ Computer Vision and Applications, 4, 1-10. http://dx.doi.org/10.2197/ipsjtcva.4.20
[12]
Rusu, R.B., Blodow, N., Marton, Z.C. and Beetz, M. (2008) Aligning Point Cloud Views Using Persistent Feature Histograms. 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, Nice, 22-26 September 2008, 3384-3391.
[13]
Sun, Y., Paik, J., Koschan, A., Page, D.L. and Abidi, M.A. (2003) Point Fingerprint: A New 3-D Object Representation Scheme. IEEE Transactions on Systems, Man, and Cybernetics, Part B, 33, 712-717. http://dx.doi.org/10.1109/TSMCB.2003.814295
[14]
Drost, B., Ulrich, M., Navab, N. and Ilic, S. (2010) Model Globally, Match Locally: Efficient and Robust 3D Object Recognition. IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, 13-18 June 2010, 998- 1005. http://dx.doi.org/10.1109/cvpr.2010.5540108
[15]
El-Khoury, S., Sahbani, A. and Perdereau, V. (2007) Learning the Natural Grasping Component of an Unknown Object. Proceedings of IEEE International Conference on Intelligent Robots and Systems, San Diego, 29 October 2007-2 November 2007, 2957-2962.
[16]
Curtis, N. and Xiao, J. (2008) Efficient and Effective Grasping of Novel Objects through Learning and Adapting a Knowledge Base. Proceedings of IEEE International Conference on Intelligent Robots and Systems, Nice, 22-26 September 2008, 2252-2257. http://dx.doi.org/10.1109/iros.2008.4651062
[17]
Morales, A., Recatala, G., Sanz, P.J. and del Pobil, A.P. (2001) Heuristic Vision-Based Computation of Planar Antipodal Grasps on Unknown Objects. Proceedings of IEEE International Conference on Intelligent Robots and Systems, 1, 583-588. http://dx.doi.org/10.1109/robot.2001.932613
[18]
Bone, G.M., Lambert, A. and Edwards, M. (2008) Automated Modeling and Robotic Grasping of Unknown Three-Dimensional Objects. Proceedings of IEEE International Conference on Robotics and Automation, Pasadena, 19-23 May 2008, 292-298. http://dx.doi.org/10.1109/robot.2008.4543223
[19]
Richtsfeld, M. and Vincze, M. (2008) Grasping of Unknown Objects from a Table Top. Proceedings of ECCV Workshop on Vision in Action: Efficient Strategies for Cognitive Agents in Complex Environments, Marseille, October 2008.
[20]
Bohg, J. and Kragic, D. (2010) Learning Grasping Points with Shape Context. Robotics and Autonomous Systems, 58, 362-377. http://dx.doi.org/10.1016/j.robot.2009.10.003
[21]
Harada, K., Kaneko, K. and Kanehiro, F. (2008) Fast Grasp Planning for Hand/Arm Systems Based on Convex Model. Proceedings of IEEE International Conference on Robotics and Automation, Pasadena, 19-23 May 2008, 1162-1168.
[22]
Harada, K., Nagta, K., Tsuji, T., Yamanobe, N., Nakamura, A. and Kawai, Y. (2013) Probabilistic Approach for Object Bin Picking Approximated by Cylinders. 2013 IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, 6-10 May 2013, 3727-3732. http://dx.doi.org/10.1109/ICRA.2013.6631103
[23]
Sanz, P.J., Requena, A., Inesta, J.M. and Del Pobil, A.P. (2005) Grasping the Not-so-Obvious: Vision-Based Object Handling for Industrial Applications. IEEE Robotics and Automation Magazine, 12, 44-52. http://dx.doi.org/10.1109/MRA.2005.1511868
[24]
Fuchs, S., Haddadin, S., Keller, M., Parusel, S., Kolb, A. and Suppa, M. (2010) Cooperative Bin-Picking with Time-of-Flight Camera and Impedance Controlled DLR Lightweight Robot III. Proceedings of IEEE International Conference on Intelligent Robots and Systems, Taipei, 18-22 October 2010, 4862-4867. http://dx.doi.org/10.1109/iros.2010.5651046
[25]
Besel, P. and McKay, N. (1992) A Method for Registration of 3-D Shapes. IEEE Transaction on Patter Analysis and Machine Intelligence, 14, 239-256.
[26]
Zhang, Z. (1994) Iterative Point Matching for Registration of Free-Form Curves and Surfaces. International Journal of Computer Vision, 13, 119-152. http://dx.doi.org/10.1007/BF01427149
[27]
Sharp, G., Lee, S. and Wehe, D. (2002) ICP Registration Using Invariant Features. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24, 90-102.
[28]
Natassha, G., Leslie, I. and Szymon, R. (2003) Geometrically Stable Sampling for the ICP Algorithm. Proceedings of the 4th International Conference on 3-D Digital Imaging and Modeling (3DIM’03), Banff, 6-10 October 2003, 260-267.
[29]
Silva, L., Olga, R. and Kim, L. (2005) Precision Range Image Registration Using a Robust Surface Interpenetration Measure and Enhanced Genetic Algorithms. IEEE Transaction on Pattern Analysis and Machine Intelligence, 27, 762-776.