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Learning robotic grasps from visual observations is a promising yet challenging task.
Planning optimal grasps
Carlo Ferrari and John F Canny · 1992
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Finding antipodal point grasps on irregularly shaped objects
I-Ming Chen and Joel W. Burdick · 1993
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Easily computable optimum grasps in 2-d and 3-d
Brian Mirtich and John Canny · 1994
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Examples of 3d grasp quality computations
Andrew T Miller and Peter K Allen · 1999
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Closure and quality equivalence for efficient synthesis of grasps from examples
Nancy S Pollard · 2004
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Rotations, quaternions, and double groups
Simon L Altmann · 2005
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Aim@shape
Bianca Falcidieno · 2005
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Coping with the grasping uncertainties in force-closure analysis
Yu Zheng and Wen-Han Qian · 2005
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Classical grasp quality evaluation: New theory and algorithms
Florian T. Pokorny and Danica Kragic · 2013
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Blender—a 3d modelling and rendering package, 2014
Blender Online Community · 2014
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Deep learning for detecting robotic grasps
Ian Lenz, Honglak Lee, and Ashutosh Saxena · 2015
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Leveraging big data for grasp planning
D. Kappler, B. Bohg, and S. Schaal · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Real-time grasp detection using convolutional neural networks
Joseph Redmon and Anelia Angelova · 2015
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Semantically-enriched 3d models for common-sense knowledge
Manolis Savva, Angel X Chang, and Pat Hanrahan · 2015
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Shapenet: An information-rich 3d model repository
Angel X Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, et al · 2015
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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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Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
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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
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Jacquard: A large scale dataset for robotic grasp detection
Amaury Depierre, Emmanuel Dellandrea, and Liming Chen · 2018
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Learning 6-dof grasping interaction via deep geometry-aware 3d representations
Xinchen Yan, Jasmine Hsu, Mohammad Khansari, Yunfei Bai, Arkanath Pathak, Abhinav Gupta, James Davidson, and Honglak Lee · 2018
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Using geometry to detect grasp poses in 3d point clouds
Andreas ten Pas and Robert Platt · 2018
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Dex-net 1.0: A cloud-based network of 3d objects for robust grasp planning using a multi-armed bandit model with correlated rewards
Jeffrey Mahler, Florian T Pokorny, Brian Hou, Melrose Roderick, Michael Laskey, Mathieu Aubry, Kai Kohlhoff, Torsten Kröger, James Kuffner, and Ken Goldberg · 2016
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You only look once: Unified, real-time object detection
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Volumetric hierarchical approximate convex decomposition
Khaled Mamou, E Lengyel, and Ed AK Peters · 2016
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Dex-net 2.0: Deep learning to plan robust grasps with synthetic point clouds and analytic grasp metrics
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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Abhinav Gupta, Adithyavairavan Murali, Dhiraj Prakashchand Gandhi, and Lerrel Pinto · 2018
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Real-world multiobject, multigrasp detection
Fu-Jen Chu, Ruinian Xu, and Patricio A Vela · 2018
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Closing the loop for robotic grasping: A real-time, generative grasp synthesis approach
Douglas Morrison, Peter Corke, and Jürgen Leitner · 2018
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Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto · 2018
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Pointnetgpd: Detecting grasp configurations from point sets
Hongzhuo Liang, Xiaojian Ma, Shuang Li, Michael Görner, Song Tang, Bin Fang, Fuchun Sun, and Jianwei Zhang · 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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Learning continuous 3d reconstructions for geometrically aware grasping
Mark Van der Merwe, Qingkai Lu, Balakumar Sundaralingam, Martin Matak, and Tucker Hermans · 2019
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