Fetching the paper…
Reading the bibliography…
In recent years, many learning based approaches have been studied to realize robotic manipulation and assembly tasks, often including vision and force/tactile feedback.
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei, “Imagenet: A large-scale hierarchical image database,” in 2009 IEEE conference on computer vision and pattern recognition . IEEE, 2009, pp. 248–255
2009
Earlier work this paper cites.
S. Giardino, F. Gori, and C. Salati, “Machine vision benchmarking,” in Workshop on Compute Vision, Italian National Association for Automation(ANIPLA) , 2012
2012
Earlier work this paper cites.
N. Correll, K. E. Bekris, D. Berenson, O. Brock, A. Causo, K. Hauser, K. Okada, A. Rodriguez, J. M. Romano, and P. R. Wurman, “Analysis and observations from the first amazon picking challenge,” IEEE Transactions on Automation Science and Engineering , vol. 15, no. 1, pp. 172–188, 2016
2016
Earlier work this paper cites.
J. Falco, J. Marvel, R. Norcross, and K. Van Wyk, “Benchmarking robot force control capabilities: Experimental results,” National Institute of Standards and Technology (NIST) , vol. 100, 2016
2016
Earlier work this paper cites.
S. Levine, C. Finn, T. Darrell, and P. Abbeel, “End-to-end training of deep visuomotor policies,” The Journal of Machine Learning Research , vol. 17, no. 1, pp. 1334–1373, 2016
2016
Earlier work this paper cites.
T. Inoue, G. De Magistris, A. Munawar, T. Yokoya, and R. Tachibana, “Deep reinforcement learning for high precision assembly tasks,” in 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2017, pp. 819–825
2017
Earlier work this paper cites.
F. Nägele, L. Halt, P. Tenbrock, and A. Pott, “A prototype-based skill model for specifying robotic assembly tasks,” in 2018 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2018, pp. 558–565
2018
Earlier work this paper cites.
M. Vecerik, T. Hester, J. Scholz, F. Wang, O. Pietquin, B. Piot, N. Heess, T. Rothörl, T. Lampe, and M. Riedmiller, “Leveraging demonstrations for deep reinforcement learning on robotics problems with sparse rewards,” 2018
2018
Cited alongside, same era.
G. Thomas, M. Chien, A. Tamar, J. A. Ojea, and P. Abbeel, “Learning robotic assembly from CAD,” in 2018 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2018, pp. 1–9
2018
Cited alongside, same era.
ABB, Application manual Force Control , ABB, 2018
2018
Cited alongside, same era.
Y. Yokokohji, Y. Kawai, M. Shibata, Y. Aiyama, S. Kotosaka, W. Uemura, A. Noda, H. Dobashi, T. Sakaguchi, and K. Yokoi, “Assembly challenge: a robot competition of the industrial robotics category, world robot summit–summary of the pre-competition in 2018,” Advanced Robotics , vol. 33, no. 17, pp. 876–899, 2019
2019
Cited alongside, same era.
F. Von Drigalski, C. Schlette, M. Rudorfer, N. Correll, J. C. Triyonoputro, W. Wan, T. Tsuji, and T. Watanabe, “Robots assembling machines: learning from the world robot summit 2018 assembly challenge,” Advanced Robotics , vol. 34, no. 7-8, pp. 408–421, 2020
2020
Later among the works it cites.
K. Kimble, K. Van Wyk, J. Falco, E. Messina, Y. Sun, M. Shibata, W. Uemura, and Y. Yokokohji, “Benchmarking protocols for evaluating small parts robotic assembly systems,” IEEE Robotics and Automation Letters , vol. 5, no. 2, pp. 883–889, 2020
2020
Later among the works it cites.
J. Watson, A. Miller, and N. Correll, “Autonomous industrial assembly using force, torque, and RGB-D sensing,” Advanced Robotics , vol. 34, no. 7-8, pp. 546–559, 2020
2020
Later among the works it cites.
G. Gorjup, G. Gao, A. Dwivedi, and M. Liarokapis, “Combining compliance control, cad based localization, and a multi-modal gripper for rapid and robust programming of assembly tasks,” 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , 2020
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
F. Hagelskjær, T. R. Savarimuthu, N. Krüger, and A. G. Buch, “Using spatial constraints for fast set-up of precise pose estimation in an industrial setting,” in 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) . IEEE, 2019, pp. 1308–1314
2019
Cited alongside, same era.
2020
Cited alongside, same era.
F. Voigt, L. Johannsmeier, and S. Haddadin, “Multi-level structure vs. end-to-end-learning in high-performance tactile robotic manipulation,” in Conference on Robot Learning . PMLR, 2020
2020
Cited alongside, same era.
2020
Later among the works it cites.
A. Carfi, M. Alameh, and F. Mastrogiovanni, “From human demonstrations to robot manipulation: a dataset for the NIST-ATB #1 benchmark,” Benchmarking Tools for Evaluating Robotic Assembly of Small Parts, Workshop at Robotics, Science and Systems(RSS) , 2020
2020
Later among the works it cites.
T. E. Lee, J. Tremblay, T. To, J. Cheng, T. Mosier, O. Kroemer, D. Fox, and S. Birchfield, “Camera-to-robot pose estimation from a single image,” IEEE International Conference on Robotics and Automation (ICRA) , 2020
2020
Later among the works it cites.