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Robotic peg-in-hole assembly remains a challenging task due to its high accuracy demand.
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M. Nigro, M. Sileo, F. Pierri, K. Genovese, D. D. Bloisi, and F. Caccavale, “Peg-in-hole using 3d workpiece reconstruction and cnn-based hole detection,” in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2020, pp. 4235–4240
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2019
Cited alongside, same era.
2019
Cited alongside, same era.
Z. Liu, L. Song, Z. Hou, K. Chen, S. Liu, and J. Xu, “Screw insertion method in peg-in-hole assembly for axial friction reduction,” IEEE Access , vol. 7, pp. 148 313–148 325, 2019
2019
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2020
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E. Y. Puang, K. P. Tee, and W. Jing, “Kovis: Keypoint-based visual servoing with zero-shot sim-to-real transfer for robotics manipulation,” in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2020, pp. 7527–7533
2020
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P. Zou, Q. Zhu, J. Wu, and R. Xiong, “Learning-based optimization algorithms combining force control strategies for peg-in-hole assembly,” in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2020, pp. 7403–7410
2020
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C. C. Beltran-Hernandez, D. Petit, I. G. Ramirez-Alpizar, and K. Harada, “Variable compliance control for robotic peg-in-hole assembly: A deep-reinforcement-learning approach,” Applied Sciences , vol. 10, no. 19, p. 6923, 2020
2020
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2020
Later among the works it cites.
E. Valassakis, N. Di Palo, and E. Johns, “Coarse-to-fine for sim-to-real: Sub-millimetre precision across wide task spaces,” in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2021, pp. 5989–5996
2021
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S. Jin, X. Zhu, C. Wang, and M. Tomizuka, “Contact pose identification for peg-in-hole assembly under uncertainties,” in 2021 American Control Conference (ACC) . IEEE, 2021, pp. 48–53
2021
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E. Johns, “Coarse-to-fine imitation learning: Robot manipulation from a single demonstration,” in 2021 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2021, pp. 4613–4619
2021
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2022
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J. Luo, E. Solowjow, C. Wen, J. A. Ojea, and A. M. Agogino, “Deep reinforcement learning for robotic assembly of mixed deformable and rigid objects,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2018, pp. 2062–2069
2069
Closest in time.