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Robotic Grasping has always been an active topic in robotics since grasping is one of the fundamental but most challenging skills of robots.
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Thea Iberall, Joe Jackson, Liz Labbe, and Ralph Zampano · 1988
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Marc Jeannerod · 1988
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Van-Duc Nguyen · 1988
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On grasp choice, grasp models, and the design of hands for manufacturing tasks
Mark R Cutkosky et al · 1989
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The multi-dimensional quality of task requirements for dextrous robot hand control
Huan Liu, Thea Iberall, and George A Bekey · 1989
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Xanthippi Markenscoff and Christos H Papadimitriou · 1989
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The geometry of grasping
Xanthippi Markenscoff, Luqun Ni, and Christos H Papadimitriou · 1990
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On computing two-finger force-closure grasps of curved 2d objects
Bernard Faverjon and Jean Ponce · 1991
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Planning optimal grasps
C Ferrari and J Canny · 1992
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Grasp synthesis of polygonal objects using a three-fingered robot hand
Young C Park and Gregory P Starr · 1992
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A system for planning and executing two-finger force-closure grasps of curved 2d objects
Darrell Stam, Jean Ponce, and Bernard Faverjon · 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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Toward automatic robot instruction from perception-recognizing a grasp from observation
Sing Bing Kang and Katsushi Ikeuchi · 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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Learning, positioning, and tracking visual appearance
Shree K Nayar, Hiroshi Murase, and Sameer A Nene · 1994
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On the closure properties of robotic grasping
Antonio Bicchi · 1995
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Support-vector networks
Corinna Cortes and Vladimir Vapnik · 1995
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Grasp metrics: Optimality and complexity
Bhubaneswar Mishra · 1995
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On computing three-finger force-closure grasps of polygonal objects
Jean Ponce and Bernard Faverjon · 1995
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Learning to grasp using visual information
Ishay Kamon, Tamar Flash, and Shimon Edelman · 1996
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On force and form closure for multiple finger grasps
Elon Rimon and Joel Burdick · 1996
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Active learning for vision-based robot grasping
Marcos Salganicoff, Lyle H Ungar, and Ruzena Bajcsy · 1996
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Robot grasp synthesis algorithms: A survey
Karun B Shimoga · 1996
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A grasp metric invariant under rigid motions
Marek Teichmann · 1996
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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On computing four-finger equilibrium and force-closure grasps of polyhedral objects
Jean Ponce, Steve Sullivan, Attawith Sudsang, Jean-Daniel Boissonnat, and Jean-Pierre Merlet · 1997
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Examples of 3d grasp quality computations
Andrew T Miller and Peter K Allen · 1999
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Computing parallel-jaw grips
Gordon Smith, Eric Lee, Ken Goldberg, Karl Bohringer, and John Craig · 1999
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Robotic grasping and contact: A review
Antonio Bicchi and Vijay Kumar · 2000
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Grasp analysis as linear matrix inequality problems
Li Han, Jeffrey C Trinkle, and Zexiang X Li · 2000
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Computing n-finger form-closure grasps on polygonal objects
Yun-Hui Liu · 2000
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Computation of 3-d form-closure grasps
Dan Ding, Yun-Hui Lee, and Shuguo Wang · 2001
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Optimal grasping based on non-dimensionalized performance indices
Byoung-Ho Kim, Sang-Rok Oh, Byung-Ju Yi, and Il Hong Suh · 2001
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Real-time tracking meets online grasp planning
Danica Kragic, Andrew T Miller, and Peter K Allen · 2001
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Learning appearance features to support robotic manipulation
Justus H. Piater and Roderic a. Grupen · 2001
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Dynamic grasp recognition within the framework of programming by demonstration
R Zollner, O Rogalla, R Dillmann, and JM Zollner · 2001
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Model based techniques for robotic servoing and grasping
Danica Kragic and Henrik I Christensen · 2002
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Ranking planar grasp configurations for a three-finger hand
Eris Chinellato, Robert B Fisher, Antonio Morales, and Angel P Del Pobil · 2003
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Object recognition and pose estimation for robotic manipulation using color cooccurrence histograms
Staffan Ekvall, Frank Hoffmann, and Danica Kragic · 2003
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Automatic grasp planning using shape primitives
Andrew T Miller, Steffen Knoop, Henrik I Christensen, and Peter K Allen · 2003
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Synthesis of force-closure grasps on 3-d objects based on the q distance
Xiangyang Zhu and Jun Wang · 2003
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Apprenticeship learning via inverse reinforcement learning
Pieter Abbeel and Andrew Y Ng · 2004
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Computation on parametric curves with an application in grasping
Yan-Bin Jia · 2004
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On quality functions for grasp synthesis, fixture planning, and coordinated manipulation
Guanfeng Liu, Jijie Xu, Xin Wang, and Zexiang Li · 2004
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Graspit! a versatile simulator for robotic grasping
Andrew T Miller and Peter K Allen · 2004
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An svm learning approach to robotic grasping
Raphael Pelossof, Andrew Miller, Peter Allen, and Tony Jebara · 2004
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Closure and quality equivalence for efficient synthesis of grasps from examples
Nancy S Pollard · 2004
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The cross-entropy method: a unified approach to combinatorial optimization, Monte-Carlo simulation, and machine learning
Reuven Y Rubinstein and Dirk P Kroese · 2004
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Visual quality measures for characterizing planar robot grasps
Eris Chinellato, Antonio Morales, Robert B Fisher, and Angel P del Pobil · 2005
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Determining independent grasp regions on 2d discrete objects
Jordi Cornella and Raúl Suárez · 2005
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Fast and flexible determination of force-closure independent regions to grasp polygonal objects
Jordi Cornella and Raúl Suárez · 2005
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Grasp recognition for programming by demonstration
Staffan Ekvall and Danica Kragic · 2005
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Estimation of hand preshaping during human grasping
Tamara Supuk, Timotej Kodek, and Tadej Bajd · 2005
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Grasp recognition in virtual reality for robot pregrasp planning by demonstration
Jacopo Aleotti and Stefano Caselli · 2006
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Learning grasp affordances through human demonstration
Charles de Granville, Joshua Southerland, and Andrew H Fagg · 2006
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Imitation learning of whole-body grasps
Kaijen Hsiao and Tomas Lozano-Perez · 2006
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Planning algorithms
Steven M LaValle · 2006
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An anthropomorphic grasping approach for an assistant humanoid robot
A Morales, P Azad, T Asfour, D Kraft, S Knoop, R Dillmann, A Kargov, CH Pylatiuk, and S Schulz · 2006
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Computing all force-closure grasps of 2d objects from contact point set
Nattee Niparnan and Attawith Sudsang · 2006
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Robotic grasping of novel objects
Ashutosh Saxena, Justin Driemeyer, Justin Kearns, and Andrew Y Ng · 2006
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Learning to grasp everyday objects using reinforcement-learning with automatic value cut-off
Tim Baier-Lowenstein and Jianwei Zhang · 2007
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Learning and evaluation of the approach vector for automatic grasp generation and planning
Staffan Ekvall and Danica Kragic · 2007
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Grasp planning via decomposition trees
Corey Goldfeder, Peter K Allen, Claire Lackner, and Raphael Pelossof · 2007
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A model of shared grasp affordances from demonstration
John D Sweeney and Rod Grupen · 2007
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Efficient and effective grasping of novel objects through learning and adapting a knowledge base
Noel Curtis and Jing Xiao · 2008
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Handling objects by their handles
Sahar El-Khoury and Anis Sahbani · 2008
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Probabilistic models of object geometry for grasp planning
Jared Glover, Daniela Rus, and Nicholas Roy · 2008
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Minimum volume bounding box decomposition for shape approximation in robot grasping
Kai Huebner, Steffen Ruthotto, and Danica Kragic · 2008
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Independent contact regions for frictional grasps on 3d objects
Máximo A Roa and Raúl Suárez · 2008
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Robotic grasping of novel objects using vision
Ashutosh Saxena, Justin Driemeyer, and Andrew Y Ng · 2008
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Manipulation planning with workspace goal regions
Dmitry Berenson, Siddhartha S Srinivasa, Dave Ferguson, Alvaro Collet, and James J Kuffner · 2009
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Grasping familiar objects using shape context
Jeannette Bohg and Danica Kragic · 2009
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Object recognition and full pose registration from a single image for robotic manipulation
Alvaro Collet, Dmitry Berenson, Siddhartha S Srinivasa, and Dave Ferguson · 2009
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Grasp recognition and mapping on humanoid robots
Martin Do, Javier Romero, Hedvig Kjellström, Pedram Azad, Tamim Asfour, Danica Kragic, and Rüdiger Dillmann · 2009
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A comprehensive grasp taxonomy
Thomas Feix, Roland Pawlik, Heinz-Bodo Schmiedmayer, Javier Romero, and Danica Kragic · 2009
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The columbia grasp database
Corey Goldfeder, Matei Ciocarlie, Hao Dang, and Peter K Allen · 2009
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Probabilistic graphical models: principles and techniques
Daphne Koller and Nir Friedman · 2009
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Computation of independent contact regions for grasping 3-d objects
Máximo A Roa and Raúl Suárez · 2009
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Learning grasping points with shape context
Jeannette Bohg and Danica Kragic · 2010
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Why does unsupervised pre-training help deep learning?
Dumitru Erhan, Aaron Courville, Yoshua Bengio, and Pascal Vincent · 2010
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Improving imitated grasping motions through interactive expected deviation learning
Kathrin Gräve, Jörg Stückler, and Sven Behnke · 2010
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Learning to grasp objects with multiple contact points
Quoc V Le, David Kamm, Arda F Kara, and Andrew Y Ng · 2010
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Grasping novel objects with depth segmentation
Deepak Rao, Quoc V Le, Thanathorn Phoka, Morgan Quigley, Attawith Sudsang, and Andrew Y Ng · 2010
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Assessing grasp stability based on learning and haptic data
Yasemin Bekiroglu, Janne Laaksonen, Jimmy Alison Jorgensen, Ville Kyrki, and Danica Kragic · 2011
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Efficient grasping from rgbd images: Learning using a new rectangle representation
Yun Jiang, Stephen Moseson, and Ashutosh Saxena · 2011
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Imitation learning of human grasping skills from motion and force data
Alexander M Schmidts, Dongheui Lee, and Angelika Peer · 2011
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Unsupervised feature learning and deep learning: A review and new perspectives
Yoshua Bengio, Aaron C Courville, and Pascal Vincent · 2012
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Learning grasp stability
Hao Dang and Peter K Allen · 2012
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Template-based learning of grasp selection
Alexander Herzog, Peter Pastor, Mrinal Kalakrishnan, Ludovic Righetti, Tamim Asfour, and Stefan Schaal · 2012
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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From caging to grasping
Alberto Rodriguez, Matthew T Mason, and Steve Ferry · 2012
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On the synthesis of feasible and prehensile robotic grasps
Carlos Rosales, Raúl Suárez, Marco Gabiccini, and Antonio Bicchi · 2012
Cited alongside, same era.
An overview of 3d object grasp synthesis algorithms
Anis Sahbani, Sahar El-Khoury, and Philippe Bidaud · 2012
Cited alongside, same era.
Learning continuous grasp stability for a humanoid robot hand based on tactile sensing
J Schill, J Laaksonen, M Przybylski, V Kyrki, T Asfour, and R Dillmann · 2012
Cited alongside, same era.
The application of particle filtering to grasping acquisition with visual occlusion and tactile sensing
Li Zhang and Jeffrey C Trinkle · 2012
Cited alongside, same era.
Simulation as an engine of physical scene understanding
Peter W Battaglia, Jessica B Hamrick, and Joshua B Tenenbaum · 2013
Cited alongside, same era.
Data-driven grasp synthesis—a survey
Jeannette Bohg, Antonio Morales, Tamim Asfour, and Danica Kragic · 2013
Learning to grasp arbitrary household objects from a single demonstration
Elias De Coninck, Tim Verbelen, Pieter Van Molle, Pieter Simoens, and Bart Dhoedt IDLab · 2019
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Deep reinforcement learning for robotic pushing and picking in cluttered environment
Yuhong Deng, Xiaofeng Guo, Yixuan Wei, Kai Lu, Bin Fang, Di Guo, Huaping Liu, and Fuchun Sun · 2019
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Learning to grasp under uncertainty using pomdps
Neha P Garg, David Hsu, and Wee Sun Lee · 2019
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Gq-stn: Optimizing one-shot grasp detection based on robustness classifier
Alexandre Gariépy, Jean-Christophe Ruel, Brahim Chaib-Draa, and Philippe Giguere · 2019
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Active vision for extraction of physically plausible support relations
Markus Grotz, David Sippel, and Tamim Asfour · 2019
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Difftaichi: Differentiable programming for physical simulation
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Cited alongside, same era.
Grounding spatial relations for human-robot interaction
Sergio Guadarrama, Lorenzo Riano, Dave Golland, Daniel Go, Yangqing Jia, Dan Klein, Pieter Abbeel, Trevor Darrell, et al · 2013
Cited alongside, same era.
Acquiring visual servoing reaching and grasping skills using neural reinforcement learning
Thomas Lampe and Martin Riedmiller · 2013
Cited alongside, same era.
Learning to parse natural language commands to a robot control system
Cynthia Matuszek, Evan Herbst, Luke Zettlemoyer, and Dieter Fox · 2013
Cited alongside, same era.
Learning support order for manipulation in clutter
Swagatika Panda, AH Abdul Hafez, and CV Jawahar · 2013
Cited alongside, same era.
Grasp moduli spaces
Florian T Pokorny, Kaiyu Hang, and Danica Kragic · 2013
Cited alongside, same era.
Open-vocabulary object retrieval
Sergio Guadarrama, Erik Rodner, Kate Saenko, Ning Zhang, Ryan Farrell, Jeff Donahue, and Trevor Darrell · 2014
Cited alongside, same era.
Yuanming Hu, Luke Anderson, Tzu-Mao Li, Qi Sun, Nathan Carr, Jonathan Ragan-Kelley, and Frédo Durand · 2019
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Chainqueen: A real-time differentiable physical simulator for soft robotics
Yuanming Hu, Jiancheng Liu, Andrew Spielberg, Joshua B Tenenbaum, William T Freeman, Jiajun Wu, Daniela Rus, and Wojciech Matusik · 2019
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Sim-to-real via sim-to-sim: Data-efficient robotic grasping via randomized-to-canonical adaptation networks
Stephen James, Paul Wohlhart, Mrinal Kalakrishnan, Dmitry Kalashnikov, Alex Irpan, Julian Ibarz, Sergey Levine, Raia Hadsell, and Konstantinos Bousmalis · 2019
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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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Active affordance exploration for robot grasping
Huaping Liu, Yuan Yuan, Yuhong Deng, Xiaofeng Guo, Yixuan Wei, Kai Lu, Bin Fang, Di Guo, and Fuchun Sun · 2019
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Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks
Jiasen Lu, Dhruv Batra, Devi Parikh, and Stefan Lee · 2019
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Multi-view picking: Next-best-view reaching for improved grasping in clutter
Douglas Morrison, Peter Corke, and Jürgen Leitner · 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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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Combining rgb and points to predict grasping region for robotic bin-picking
Quanquan Shao and Jie Hu · 2019
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Suction grasp region prediction using self-supervised learning for object picking in dense clutter
Quanquan Shao, Jie Hu, Weiming Wang, Yi Fang, Wenhai Liu, Jin Qi, and Jin Ma · 2019
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Vl-bert: Pre-training of generic visual-linguistic representations
Weijie Su, Xizhou Zhu, Yue Cao, Bin Li, Lewei Lu, Furu Wei, and Jifeng Dai · 2019
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Efficient fully convolution neural network for generating pixel wise robotic grasps with high resolution images
Shengfan Wang, Xin Jiang, Jie Zhao, Xiaoman Wang, Weiguo Zhou, and Yunhui Liu · 2019
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Multimodal grasp data set: A novel visual–tactile data set for robotic manipulation
Tao Wang, Chao Yang, Frank Kirchner, Peng Du, Fuchun Sun, and Bin Fang · 2019
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Learning virtual grasp with failed demonstrations via bayesian inverse reinforcement learning
Xu Xie, Changyang Li, Chi Zhang, Yixin Zhu, and Song-Chun Zhu · 2019
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Data-efficient learning for sim-to-real robotic grasping using deep point cloud prediction networks
Xinchen Yan, Mohi Khansari, Jasmine Hsu, Yuanzheng Gong, Yunfei Bai, Sören Pirk, and Honglak Lee · 2019
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A multi-task convolutional neural network for autonomous robotic grasping in object stacking scenes
Hanbo Zhang, Xuguang Lan, Site Bai, Lipeng Wan, Chenjie Yang, and Nanning Zheng · 2019
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Roi-based robotic grasp detection for object overlapping scenes
Hanbo Zhang, Xuguang Lan, Site Bai, Xinwen Zhou, Zhiqiang Tian, and Nanning Zheng · 2019
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A real-time robotic grasping approach with oriented anchor box
Hanbo Zhang, Xinwen Zhou, Xuguang Lan, Jin Li, Zhiqiang Tian, and Nanning Zheng · 2019
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Self-supervised learning for precise pick-and-place without object model
Lars Berscheid, Pascal Meißner, and Torsten Kröger · 2020
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Learning one-shot imitation from humans without humans
Alessandro Bonardi, Stephen James, and Andrew J Davison · 2020
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Orientation attentive robotic grasp synthesis with augmented grasp map representation
Georgia Chalvatzaki, Nikolaos Gkanatsios, Petros Maragos, and Jan Peters · 2020
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Transferable active grasping and real embodied dataset
Xiangyu Chen, Zelin Ye, Jiankai Sun, Yuda Fan, Fang Hu, Chenxi Wang, and Cewu Lu · 2020
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Uniter: Universal image-text representation learning
Yen-Chun Chen, Linjie Li, Licheng Yu, Ahmed El Kholy, Faisal Ahmed, Zhe Gan, Yu Cheng, and Jingjing Liu · 2020
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Towards generalization and data efficient learning of deep robotic grasping
Zhixin Chen, Mengxiang Lin, Zhixin Jia, and Shibo Jian · 2020
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Transformers for one-shot visual imitation
Sudeep Dasari and Abhinav Gupta · 2020
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Graspnet-1billion: A large-scale benchmark for general object grasping
Hao-Shu Fang, Chenxi Wang, Minghao Gou, and Cewu Lu · 2020
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Orientation attentive robot grasp synthesis
Nikolaos Gkanatsios, Georgia Chalvatzaki, Petros Maragos, and Jan Peters · 2020
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Toward sim-to-real directional semantic grasping
Shariq Iqbal, Jonathan Tremblay, Andy Campbell, Kirby Leung, Thang To, Jia Cheng, Erik Leitch, Duncan McKay, and Stan Birchfield · 2020
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Self-supervised visual feature learning with deep neural networks: A survey
Longlong Jing and Yingli Tian · 2020
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A survey on learning-based robotic grasping
Kilian Kleeberger, Richard Bormann, Werner Kraus, and Marco F Huber · 2020
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Learning to grasp 3d objects using deep residual u-nets
Yikun Li, Lambert Schomaker, and S Hamidreza Kasaei · 2020
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Deep learning for generic object detection: A survey
Li Liu, Wanli Ouyang, Xiaogang Wang, Paul Fieguth, Jie Chen, Xinwang Liu, and Matti Pietikäinen · 2020
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Learning robust, real-time, reactive robotic grasping
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6-dof grasping for target-driven object manipulation in clutter
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Pointnet++ grasping: Learning an end-to-end spatial grasp generation algorithm from sparse point clouds
Peiyuan Ni, Wenguang Zhang, Xiaoxiao Zhu, and Qixin Cao · 2020
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A survey of the usages of deep learning for natural language processing
Daniel W Otter, Julian R Medina, and Jugal K Kalita · 2020
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Real-time, highly accurate robotic grasp detection using fully convolutional neural network with rotation ensemble module
Dongwon Park, Yonghyeok Seo, and Se Young Chun · 2020
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A single multi-task deep neural network with post-processing for object detection with reasoning and robotic grasp detection
Dongwon Park, Yonghyeok Seo, Dongju Shin, Jaesik Choi, and Se Young Chun · 2020
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S4g: Amodal single-view single-shot se (3) grasp detection in cluttered scenes
Yuzhe Qin, Rui Chen, Hao Zhu, Meng Song, Jing Xu, and Hao Su · 2020
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Unigrasp: Learning a unified model to grasp with multifingered robotic hands
Lin Shao, Fabio Ferreira, Mikael Jorda, Varun Nambiar, Jianlan Luo, Eugen Solowjow, Juan Aparicio Ojea, Oussama Khatib, and Jeannette Bohg · 2020
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Ingress: Interactive visual grounding of referring expressions
Mohit Shridhar, Dixant Mittal, and David Hsu · 2020
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A novel robotic grasp detection method based on region proposal networks
Yanan Song, Liang Gao, Xinyu Li, and Weiming Shen · 2020
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Grasp proposal networks: An end-to-end solution for visual learning of robotic grasps
Chaozheng Wu, Jian Chen, Qiaoyu Cao, Jianchi Zhang, Yunxin Tai, Lin Sun, and Kui Jia · 2020
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A comprehensive survey on graph neural networks
Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, and S Yu Philip · 2020
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Learning rgb-d feature embeddings for unseen object instance segmentation
Yu Xiang, Christopher Xie, Arsalan Mousavian, and Dieter Fox · 2020
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Visual manipulation relationship recognition in object-stacking scenes
Hanbo Zhang, Xuguang Lan, Xinwen Zhou, Zhiqiang Tian, Yang Zhang, and Nanning Zheng · 2020
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Deep learning on graphs: A survey
Ziwei Zhang, Peng Cui, and Wenwu Zhu · 2020
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Amodal 3d reconstruction for robotic manipulation via stability and connectivity
William Agnew, Christopher Xie, Aaron Walsman, Octavian Murad, Yubo Wang, Pedro Domingos, and Siddhartha Srinivasa · 2021
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Depth-aware object segmentation and grasp detection for robotic picking tasks
Stefan Ainetter, Christoph Böhm, Rohit Dhakate, Stephan Weiss, and Friedrich Fraundorfer · 2021
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End-to-end trainable deep neural network for robotic grasp detection and semantic segmentation from rgb
Stefan Ainetter and Friedrich Fraundorfer · 2021
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Suctionnet-1billion: A large-scale benchmark for suction grasping
Hanwen Cao, Hao-Shu Fang, Wenhai Liu, and Cewu Lu · 2021
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Ab initio particle-based object manipulation
Siwei Chen, Xiao Ma, Yunfan Lu, and David Hsu · 2021
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A joint network for grasp detection conditioned on natural language commands
Yiye Chen, Ruinian Xu, Yunzhi Lin, and Patricio A Vela · 2021
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A comprehensive study of 3-d vision-based robot manipulation
Yang Cong, Ronghan Chen, Bingtao Ma, Hongsen Liu, Dongdong Hou, and Chenguang Yang · 2021
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Real-world semantic grasping detection
Mingshuai Dong, Shimin Wei, Jianqin Yin, and Xiuli Yu · 2021
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Mask-gd segmentation based robotic grasp detection
Mingshuai Dong, Shimin Wei, Xiuli Yu, and Jianqin Yin · 2021
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Acronym: A large-scale grasp dataset based on simulation
Clemens Eppner, Arsalan Mousavian, and Dieter Fox · 2021
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Integrated task and motion planning
Caelan Reed Garrett, Rohan Chitnis, Rachel Holladay, Beomjoon Kim, Tom Silver, Leslie Pack Kaelbling, and Tomás Lozano-Pérez · 2021
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Rgb matters: Learning 7-dof grasp poses on monocular rgbd images
Minghao Gou, Hao-Shu Fang, Zhanda Zhu, Sheng Xu, Chenxi Wang, and Cewu Lu · 2021
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Graspme-grasp manifold estimator
Janik Hager, Ruben Bauer, Marc Toussaint, and Jim Mainprice · 2021
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Learning suction graspability considering grasp quality and robot reachability for bin-picking
Ping Jiang, Junji Oaki, Yoshiyuki Ishihara, Junichiro Ooga, Haifeng Han, Atsushi Sugahara, Seiji Tokura, Haruna Eto, Kazuma Komoda, and Akihito Ogawa · 2021
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Mvgrasp: Real-time multi-view 3d object grasping in highly cluttered environments
Hamidreza Kasaei and Mohammadreza Kasaei · 2021
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Simultaneous multi-view object recognition and grasping in open-ended domains
Hamidreza Kasaei, Sha Luo, Remo Sasso, and Mohammadreza Kasaei · 2021
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A review of robot learning for manipulation: Challenges, representations, and algorithms
Oliver Kroemer, Scott Niekum, and George Konidaris · 2021
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Simultaneous semantic and collision learning for 6-dof grasp pose estimation
Yiming Li, Tao Kong, Ruihang Chu, Yifeng Li, Peng Wang, and Lei Li · 2021
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Language conditioned imitation learning over unstructured data
Corey Lynch and Pierre Sermanet · 2021
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