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Grasping unseen objects in unconstrained, cluttered environments is an essential skill for autonomous robotic manipulation.
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C. Wang, D. Xu, Y. Zhu, R. Martín-Martín, C. Lu, L. Fei-Fei, and S. Savarese, “Densefusion: 6d object pose estimation by iterative dense fusion,” 2019
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2019
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C. Xie, Y. Xiang, A. Mousavian, and D. Fox, “The best of both modes: Separately leveraging rgb and depth for unseen object instance segmentation,” in Conference on Robot Learning (CoRL) , 2019
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2019
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2019
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2020
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M. Breyer, J. J. Chung, L. Ott, R. Siegwart, and J. Nieto, “Volumetric grasping network: Real-time 6 dof grasp detection in clutter,” 2021
2021
Closest in time.
C. Eppner, A. Mousavian, and F. Dieter, “Acronym: A large-scale grasp dataset based on simulation,” IEEE International Conference on Robotics and Automation (ICRA) , 2021
2021
Closest in time.
M. Danielczuk, A. Mousavian, C. Eppner, and D. Fox, “Object rearrangement using learned implicit collision functions,” in 2021 IEEE International Conference on Robotics and Automation (ICRA) , 2021
2021
Closest in time.