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Grasp detection in clutter requires the robot to reason about the 3D scene from incomplete and noisy perception.
Marching cubes: A high resolution 3d surface construction algorithm
William E Lorensen and Harvey E Cline · 1987
Earlier work this paper cites.
Planning optimal grasps
Carlo Ferrari and John F Canny · 1992
Earlier work this paper cites.
On characterizing and computing three-and four-finger force-closure grasps of polyhedral objects
Jean Ponce, Steve Sullivan, J-D Boissonnat, and J-P Merlet · 1993
Earlier work this paper cites.
Easily computable optimum grasps in 2-d and 3-d
Brian Mirtich and John Canny · 1994
Earlier work this paper cites.
A volumetric method for building complex models from range images
Brian Curless and Marc Levoy · 1996
Earlier work this paper cites.
Qualitative test and force optimization of 3-d frictional form-closure grasps using linear programming
Yun-Hui Liu · 1999
Earlier work this paper cites.
Computing 3-d optimal form-closure grasps
Dan Ding, Yun-Hui Liu, and Shuguo Wang · 2000
Earlier work this paper cites.
Real-time tracking meets online grasp planning
Danica Kragic, Andrew T Miller, and Peter K Allen · 2001
Earlier work this paper cites.
Planning force-closure grasps on 3-d objects
Xiangyang Zhu and Han Ding · 2004
Earlier work this paper cites.
Real-time cad model matching for mobile manipulation and grasping
Ulrich Klank, Dejan Pangercic, Radu Bogdan Rusu, and Michael Beetz · 2009
Earlier work this paper cites.
Learning grasping points with shape context
Jeannette Bohg and Danica Kragic · 2010
Earlier work this paper cites.
Mind the gap-robotic grasping under incomplete observation
Jeannette Bohg, Matthew Johnson-Roberson, Beatriz León, Javier Felip, Xavi Gratal, Niklas Bergström, Danica Kragic, and Antonio Morales · 2011
Earlier work this paper cites.
Efficient grasping from rgbd images: Learning using a new rectangle representation
Yun Jiang, Stephen Moseson, and Ashutosh Saxena · 2011
Earlier work this paper cites.
The kit object models database: An object model database for object recognition, localization and manipulation in service robotics
Alexander Kasper, Zhixing Xue, and Rüdiger Dillmann · 2012
Earlier work this paper cites.
From caging to grasping
Alberto Rodriguez, Matthew T Mason, and Steve Ferry · 2012
Earlier work this paper cites.
An overview of 3d object grasp synthesis algorithms
Anis Sahbani, Sahar El-Khoury, and Philippe Bidaud · 2012
Earlier work this paper cites.
Data-driven grasp synthesis—a survey
Jeannette Bohg, Antonio Morales, Tamim Asfour, and Danica Kragic · 2013
Earlier work this paper cites.
Learning grasps for unknown objects in cluttered scenes
David Fischinger, Markus Vincze, and Yun Jiang · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Bigbird: A large-scale 3d database of object instances
Arjun Singh, James Sha, Karthik S Narayan, Tudor Achim, and Pieter Abbeel · 2014
Earlier work this paper cites.
The ycb object and model set: Towards common benchmarks for manipulation research
Berk Calli, Arjun Singh, Aaron Walsman, Siddhartha Srinivasa, Pieter Abbeel, and Aaron M Dollar · 2015
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Leveraging big data for grasp planning
Daniel Kappler, Jeannette Bohg, and Stefan Schaal · 2015
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Exploiting symmetries and extrusions for grasping household objects
Ana Huamán Quispe, Benoît Milville, Marco A Gutiérrez, Can Erdogan, Mike Stilman, Henrik Christensen, and Heni Ben Amor · 2015
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U-Net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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High precision grasp pose detection in dense clutter
Marcus Gualtieri, Andreas Ten Pas, Kate Saenko, and Robert Platt · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Robust grasp planning over uncertain shape completions
Jens Lundell, Francesco Verdoja, and Ville Kyrki · 2019
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Learning ambidextrous robot grasping policies
Jeffrey Mahler, Matthew Matl, Vishal Satish, Michael Danielczuk, Bill DeRose, Stephen McKinley, and Ken Goldberg · 2019
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Occupancy networks: Learning 3d reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
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6-dof graspnet: Variational grasp generation for object manipulation
Arsalan Mousavian, Clemens Eppner, and Dieter Fox · 2019
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Deepsdf: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
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Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours
Lerrel Pinto and Abhinav Gupta · 2016
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Affordance detection for task-specific grasping using deep learning
Mia Kokic, Johannes A Stork, Joshua A Haustein, and Danica Kragic · 2017
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Jeffrey Mahler, Jacky Liang, Sherdil Niyaz, Michael Laskey, Richard Doan, Xinyu Liu, Juan Aparicio Ojea, and Ken Goldberg · 2017
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Grasp pose detection in point clouds
Andreas ten Pas, Marcus Gualtieri, Kate Saenko, and Robert Platt · 2017
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Shape completion enabled robotic grasping
Jacob Varley, Chad DeChant, Adam Richardson, Joaquín Ruales, and Peter Allen · 2017
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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
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
Later among the works it cites.
Disn: Deep implicit surface network for high-quality single-view 3d reconstruction
Qiangeng Xu, Weiyue Wang, Duygu Ceylan, Radomir Mech, and Ulrich Neumann · 2019
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Volumetric grasping network: Real-time 6 dof grasp detection in clutter
Michel Breyer, Jen Jen Chung, Lionel Ott, Siegwart Roland, and Nieto Juan · 2020
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Implicit functions in feature space for 3d shape reconstruction and completion
Julian Chibane, Thiemo Alldieck, and Gerard Pons-Moll · 2020
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Learning task-oriented grasping for tool manipulation from simulated self-supervision
Kuan Fang, Yuke Zhu, Animesh Garg, Andrey Kurenkov, Viraj Mehta, Li Fei-Fei, and Silvio Savarese · 2020
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Local deep implicit functions for 3d shape
Kyle Genova, Forrester Cole, Avneesh Sud, Aaron Sarna, and Thomas Funkhouser · 2020
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Lingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua, and Christian Theobalt · 2020
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Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P Srinivasan, Matthew Tancik, Jonathan T Barron, Ravi Ramamoorthi, and Ren Ng · 2020
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NVISII: Nvidia scene imaging interface, 2020
Nathan Morrical, Jonathan Tremblay, Stan Birchfield, and Ingo Wald · 2020
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Convolutional occupancy networks
Songyou Peng, Michael Niemeyer, Lars Mescheder, Marc Pollefeys, and Andreas Geiger · 2020
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Affordance-based grasping and manipulation in real world applications
Christoph Pohl, Kevin Hitzler, Raphael Grimm, Antonio Zea, Uwe D Hanebeck, and Tamim Asfour · 2020
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Implicit neural representations with periodic activation functions
Vincent Sitzmann, Julien NP Martel, Alexander W Bergman, David B Lindell, and Gordon Wetzstein · 2020
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Learning continuous 3d reconstructions for geometrically aware grasping
Mark Van der Merwe, Qingkai Lu, Balakumar Sundaralingam, Martin Matak, and Tucker Hermans · 2020
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Learning to see before learning to act: Visual pre-training for manipulation
Lin Yen-Chen, Andy Zeng, Shuran Song, Phillip Isola, and Tsung-Yi Lin · 2020
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