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Robots need the capability of placing objects in arbitrary, specific poses to rearrange the world and achieve various valuable tasks.
Regrasping
Pierre Tournassoud, Tomás Lozano-Pérez, and Emmanuel Mazer · 1987
Earlier work this paper cites.
Dynamic control of sliding by robot hands for regrasping
Arlene A Cole, Ping Hsu, and S Shankar Sastry · 1992
Earlier work this paper cites.
Generating and evaluating regrasp operations
F Rohrdanz and Friedrich M Wahl · 1997
Earlier work this paper cites.
Robotic grasping and contact: A review
Antonio Bicchi and Vijay Kumar · 2000
Earlier work this paper cites.
RRT-connect: An efficient approach to single-query path planning
James J Kuffner and Steven M LaValle · 2000
Earlier work this paper cites.
ROS: an open-source robot operating system
Morgan Quigley, Ken Conley, Brian Gerkey, Josh Faust, Tully Foote, Jeremy Leibs, Rob Wheeler, and Andrew Y Ng · 2009
Earlier work this paper cites.
The open motion planning library
Ioan Alexandru Sucan, Mark Moll, and Lydia E Kavraki · 2012
Earlier work this paper cites.
Extrinsic dexterity: In-hand manipulation with external forces
Nikhil Chavan Dafle, Alberto Rodriguez, Robert Paolini, Bowei Tang, Siddhartha S Srinivasa, Michael Erdmann, Matthew T Mason, Ivan Lundberg, Harald Staab, and Thomas Fuhlbrigge · 2014
Earlier work this paper cites.
A constraint-based method for solving sequential manipulation planning problems
Tomás Lozano-Pérez and Leslie Pack Kaelbling · 2014
Earlier work this paper cites.
The YCB object and Model set: Towards common benchmarks for manipulation research
B. Calli, A. Singh, A. Walsman, P Srinivasa S. and, Abbeel, and A. M. Dollar · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
Probabilistic multi-class segmentation for the amazon picking challenge
Rico Jonschkowski, Clemens Eppner, Sebastian Höfer, Roberto Martín-Martín, and Oliver Brock · 2016
Earlier work this paper cites.
End-to-end training of deep visuomotor policies
Sergey Levine, Chelsea Finn, Trevor Darrell, and Pieter Abbeel · 2016
Earlier work this paper cites.
Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours
Lerrel Pinto and Abhinav Gupta · 2016
Cited alongside, same era.
Achieving high success rate in dual-arm handover using large number of candidate grasps, handover heuristics, and hierarchical search
Weiwei Wan and Kensuke Harada · 2016
Cited alongside, same era.
Developing and comparing single-arm and dual-arm regrasp
Weiwei Wan and Kensuke Harada · 2016
Cited alongside, same era.
Intel realsense stereoscopic depth cameras
Leonid Keselman, John Iselin Woodfill, Anders Grunnet-Jepsen, and Achintya Bhowmik · 2017
Cited alongside, same era.
Multi-view self-supervised deep learning for 6d pose estimation in the amazon picking challenge
Andy Zeng, Kuan-Ting Yu, Shuran Song, Daniel Suo, Ed Walker, Alberto Rodriguez, and Jianxiong Xiao · 2017
Cited alongside, same era.
Pick and place without geometric object models
Towards robust product packing with a minimalistic end-effector
Rahul Shome, Wei N Tang, Changkyu Song, Chaitanya Mitash, Hristiyan Kourtev, Jingjin Yu, Abdeslam Boularias, and Kostas E Bekris · 2019
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A regrasp planning component for object reorientation
Weiwei Wan, Hisashi Igawa, Kensuke Harada, Hiromu Onda, Kazuyuki Nagata, and Natsuki Yamanobe · 2019
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DenseFusion: 6D object pose estimation by iterative dense fusion
Chen Wang, Danfei Xu, Yuke Zhu, Roberto Martín-Martín, Cewu Lu, Li Fei-Fei, and Silvio Savarese · 2019
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Learning dexterous in-hand manipulation
Marcin Andrychowicz, Bowen Baker, Maciek Chociej, Rafal Jozefowicz, Bob McGrew, Jakub Pachocki, Arthur Petron, Matthias Plappert, Glenn Powell, Alex Ray, et al · 2020
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Rearrangement: A challenge for embodied AI
D. Batra, A. X. Chang, S. Chernova, A. J. Davison, J. Deng, V. Koltun, S. Levine, J. Malik, I. Mordatch, R. Mottaghi, M. Savva, and H. Su · 2020
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Marcus Gualtieri, Andreas ten Pas, and Robert Platt · 2018
Cited alongside, same era.
QT-Opt: Scalable deep reinforcement learning for vision-based robotic manipulation
Dmitry Kalashnikov, Alex Irpan, Peter Pastor, Julian Ibarz, Alexander Herzog, Eric Jang, Deirdre Quillen, Ethan Holly, Mrinal Kalakrishnan, Vincent Vanhoucke, et al · 2018
Cited alongside, same era.
Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection
Sergey Levine, Peter Pastor, Alex Krizhevsky, Julian Ibarz, and Deirdre Quillen · 2018
Cited alongside, same era.
Instance segmentation of visible and occluded regions for finding and picking target from a pile of objects
Kentaro Wada, Shingo Kitagawa, Kei Okada, and Masayuki Inaba · 2018
Cited alongside, same era.
Robotic pick-and-place of novel objects in clutter with multi-affordance grasping and cross-domain image matching
Andy Zeng, Shuran Song, Kuan-Ting Yu, Elliott Donlon, Francois R Hogan, Maria Bauza, Daolin Ma, Orion Taylor, Melody Liu, Eudald Romo, et al · 2018
Cited alongside, same era.
Solving rubik’s cube with a robot hand
Ilge Akkaya, Marcin Andrychowicz, Maciek Chociej, Mateusz Litwin, Bob McGrew, Arthur Petron, Alex Paino, Matthias Plappert, Glenn Powell, Raphael Ribas, et al · 2019
Cited alongside, same era.
kPAM: Keypoint affordances for category-level robotic manipulation
Lucas Manuelli, Wei Gao, Peter Florence, and Russ Tedrake · 2019
Cited alongside, same era.
Task-driven perception and manipulation for constrained placement of unknown objects
Chaitanya Mitash, Rahul Shome, Bowen Wen, Abdeslam Boularias, and Kostas Bekris · 2020
Later among the works it cites.
MoreFusion: Multi-object reasoning for 6D pose estimation from volumetric fusion
Kentaro Wada, Edgar Sucar, Stephen James, Daniel Lenton, and Andrew J. Davison · 2020
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Transporter networks: Rearranging the visual world for robotic manipulation
Andy Zeng, Pete Florence, Jonathan Tompson, Stefan Welker, Jonathan Chien, Maria Attarian, Travis Armstrong, Ivan Krasin, Dan Duong, Vikas Sindhwani, et al · 2020
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Learning to regrasp by learning to place
Shuo Cheng, Kaichun Mo, and Lin Shao · 2021
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PyBullet, a python module for physics simulation for games, robotics and machine learning
Erwin Coumans and Yunfei Bai · 2021
Later among the works it cites.
Coarse-to-Fine Q-attention: Efficient learning for visual robotic manipulation via discretisation
Stephen James, Kentaro Wada, Tristan Laidlow, and Andrew J Davison · 2021
Later among the works it cites.
SafePicking: Learning safe object extraction via object-level mapping
Kentaro Wada, Stephen James, and Andrew J. Davison · 2022
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