340
Views
1
CrossRef citations to date
0
Altmetric
Research Article

Virtual training and commissioning of industrial bin picking systems using synthetic sensor data and simulation

, , , , , , & ORCID Icon show all
Pages 483-492 | Received 15 Jun 2020, Accepted 26 Oct 2021, Published online: 03 Dec 2021

References

  • Blank, A., M. Hiller, S. Zhang, A. Leser, M. Metzner, M. Lieret, J. Thielecke, and J. Franke. 2019. “6DoF Pose-Estimation Pipeline for Texture-less Industrial Components in Bin Picking Applications.” In 2019 European Conference on Mobile Robots (ECMR), 1–7. Prague: IEEE.
  • Dietrich, V., B. Kast, S. Albrecht, and M. Beetz. 2020. “Data-Driven Synthesis of Perception Pipelines via Hierarchical Planning.” In Advances in Service and Industrial Robotics. Vol. 84, edited by S. Zeghloul, M. A. Laribi, and J. S. Sandoval Arevalo, 516–524. Mechanisms and Machine Science. Cham: Springer International Publishing.
  • Fur, S., A. Verl, and A. Pott. 2018. “Simulation of Industrial Bin Picking: An Application of Laser Range Finder Simulation.” In 2018 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), 1–6. Ottawa.
  • Fur, S., B. Boughattas, A. Verl, and A. Pott. 2020. “Prediction of the Configuration of Objects in a Bin Based on Synthetic Sensor Data.” Procedia CIRP 88: 54–59. doi:https://doi.org/10.1016/j.procir.2020.05.010.
  • Hinterstoisser, S., V. Lepetit, P. Wohlhart, and K. Konolige. 2019. “On Pre-trained Image Features and Synthetic Images for Deep Learning.” In Computer Vision - ECCV 2018 Workshops: Munich, Germany, September 814, 2018: Proceedings. Vol. 11129, edited by L. Leal-Taixé and S. Roth, 682–697. Lecture Notes in Computer Science 11129. Cham: Springer.
  • Hodaň, T., F. Michel, E. Brachmann, A. G. Wadim Kehl, D. K. Buch, B. Drost, et al. 2018. “BOP: Benchmark for 6D Object Pose Estimation.” In Computer Vision - ECCV 2018: 15th European Conference, Munich, Germany, September 8–14, 2018: proceedings. Vol. 11214, edited by V. Ferrari, 19–35. LNCS sublibrary: SL6 Image processing, computer vision, pattern recognition, and graphics . LNCS sublibrary: SL6 Image processing, computer vision, pattern recognition, and graphics 1120511220. 1120511220. Cham, Switzerland: Springer.
  • Hodaň, T., V. Vineet, R. Gal, E. Shalev, J. Hanzelka, T. Connell, P. Urbina, S. Sinha, and B. Guenter. 2019. “Photorealistic Image Synthesis for Object Instance Detection.” IEEE International Conference on Image Processing (ICIP) 66–70.
  • Holz, D., A. E. Ichim, F. Tombari, R. B. Rusu, and S. Behnke. 2015. “Registration with the Point Cloud Library: A Modular Framework for Aligning in 3-D.” IEEE Robotics & Automation Magazine 22 (4): 110–124. doi:https://doi.org/10.1109/MRA.2015.2432331.
  • Imperoli, M., and A. Pretto. 2015. “D2CO: Fast and Robust Registration of 3D Textureless Objects Using the Directional Chamfer Distance.” In Computer Vision Systems. Vol. 9163, edited by L. Nalpantidis, V. Krueger, J.-O. Eklundh, and A. Gasteratos, 316–328. Lecture Notes in Computer Science 9163. Cham: Springer.
  • Metzner, M., S. Weissert, E. Karlidag, F. Albrecht, A. Blank, A. Mayr, and J. Franke. 2019. “Virtual Commissioning of 6 DoF Pose Estimation and Robotic Bin Picking Systems for Industrial Parts.” IFAC-PapersOnLine 52 (10): 160–164. doi:https://doi.org/10.1016/j.ifacol.2019.10.040.
  • PapersWithCode. 2021. “6D Pose Estimation Using RGB on LineMOD.” Accessed 11 September 2020. https://paperswithcode.com/sota/6d-pose-estimation-on-linemod
  • Quigley, M., B. Gerkey, K. Conley, J. Faust, T. Foote, J. Leibs, E. Berger, R. Wheeler, and A. Ng. 2009. “ROS: An Open-source Robot Operating System.” In Proc. of the IEEE Intl. Conf. on Robotics and Automation (ICRA) Workshop on Open Source Robotics. Kobe, Japan.
  • Roberts, L. G. 1963. “Machine Perception of Three-dimensional Solids.” Thesis (Ph. D.), Department of Electrical Engineering, Massachusetts Institute of Technology. Accessed 02 April 2019. http://hdl.handle.net/1721.1/11589
  • Schyja, A., A. Hypki, and B. Kuhlenkötter. 2012. “A Modular and Extensible Framework for Real and Virtual Bin-picking Environments.” In Robotics and Automation (ICRA), 2012 IEEE International Conference, 5246–5251. Saint Paul, MN.
  • Schyja, A., and B. Kuhlenkötter. 2014. “Virtual Bin Picking - a Generic Framework to Overcome the Bin Picking Complexity by the Use of a Virtual Environment.” In Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH), 2014 International Conference. Vienna, Austria.
  • Schyja, A., and B. Kuhlenkötter. 2015. “Realistic Simulation of Industrial Bin-Picking Systems: 17-19 Feb. 2015, Queenstown, New Zealand.” http://ieeexplore.ieee.org/servlet/opac?punumber=7066220
  • Tekin, B., S. N. Sinha, and P. Fua. 2018. “Real-Time Seamless Single Shot 6D Object Pose Prediction.” In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 292–301. Salt Lake City, UT: IEEE.
  • To, T., J. Tremblay, D. McKay, Y. Yamaguchi, K. Leung, A. Balanon, J. Cheng, W. Hodge, and S. Birchfield. 2018. NDDS: NVIDIA Deep Learning Dataset Synthesizer. Github.
  • Tobin, J., R. Fong, A. Ray, J. Schneider, W. Zaremba, and P. Abbeel. 2017. “Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World.” http://arxiv.org/pdf/1703.06907v1

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.