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Tool manipulation is vital for facilitating robots to complete challenging task goals.
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Richard Hartley and Andrew Zisserman · 2003
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Reuven Y Rubinstein and Dirk P Kroese · 2004
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Shunsuke Komizunai, Fumiya Nishii’ Teppei Tsujita, Yuki Nomura, and Takuya Owa · 2008
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Ashutosh Saxena, Justin Driemeyer, and Andrew Y Ng · 2008
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Matei T Ciocarlie and Peter K Allen · 2009
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Corey Goldfeder, Matei Ciocarlie, Hao Dang, and Peter K Allen · 2009
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Khaled Mamou and Faouzi Ghorbel · 2009
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François Osiurak, Christophe Jarry, and Didier Le Gall · 2010
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Learning task constraints for robot grasping using graphical models
Dan Song, Kai Huebner, Ville Kyrki, and Danica Kragic · 2010
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A framework for push-grasping in clutter
Mehmet Dogar and Siddhartha Srinivasa · 2011
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Learning of tool affordances for autonomous tool manipulation
Raghvendra Jain and Tetsunari Inamura · 2011
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Tool use and learning in robots
Solly Brown and Claude Sammut · 2012
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Semantic grasping: Planning robotic grasps functionally suitable for an object manipulation task
Hao Dang and Peter K Allen · 2012
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Learning object arrangements in 3d scenes using human context
Yun Jiang, Marcus Lim, and Ashutosh Saxena · 2012
Understanding tools: Task-oriented object modeling, learning and recognition
Yixin Zhu, Yibiao Zhao, and Song Chun Zhu · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Grasping for a purpose: Using task goals for efficient manipulation planning
Ana Huaman Quispe, Heni Ben Amor, Henrik Christensen, and Mike Stilman · 2016
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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 · 2016
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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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From caging to grasping
Alberto Rodriguez, Matthew T Mason, and Steve Ferry · 2012
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Afrob: The affordance network ontology for robots
Karthik Mahesh Varadarajan and Markus Vincze · 2012
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Pose error robust grasping from contact wrench space metrics
Jonathan Weisz and Peter K Allen · 2012
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A survey of the ontogeny of tool use: from sensorimotor experience to planning
Frank Guerin, Norbert Kruger, and Dirk Kraft · 2013
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Learning human activities and object affordances from RGB-D videos
Hema Swetha Koppula, Rudhir Gupta, and Ashutosh Saxena · 2013
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Data-driven grasp synthesis – a survey
Jeannette Bohg, Antonio Morales, Tamim Asfour, and Danica Kragic · 2014
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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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Using simulation and domain adaptation to improve efficiency of deep robotic grasping
Konstantinos Bousmalis, Alex Irpan, Paul Wohlhart, Yunfei Bai, Matthew Kelcey, Mrinal Kalakrishnan, Laura Downs, Julian Ibarz, Peter Pastor, Kurt Konolige, et al · 2017
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pybullet, a python module for physics simulation, games, robotics and machine learning
Erwin Coumans and Yunfei Bai · 2017
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Affordancenet: An end-to-end deep learning approach for object affordance detection
Thanh-Toan Do, Anh Nguyen, Ian Reid, Darwin G Caldwell, and Nikos G Tsagarakis · 2017
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Learning to singulate objects using a push proposal network
Andreas Eitel, Nico Hauff, and Wolfram Burgard · 2017
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End-to-end learning of semantic grasping
Eric Jang, Sudheendra Vijaynarasimhan, Peter Pastor, Julian Ibarz, and Sergey Levine · 2017
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Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations
Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin Jamieson, Anca Dragan, and Ken Goldberg · 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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Self-supervised learning of tool affordances from 3d tool representation through parallel som mapping
Tanis Mar, Vadim Tikhanoff, Giorgio Metta, and Lorenzo Natale · 2017
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Domain randomization and generative models for robotic grasping
Joshua Tobin, Wojciech Zaremba, and Pieter Abbeel · 2017
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Learning a visuomotor controller for real world robotic grasping using easily simulated depth images
Ulrich Viereck, Andreas ten Pas, Kate Saenko, and Robert Platt · 2017
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Multi-task domain adaptation for deep learning of instance grasping from simulation
Kuan Fang, Yunfei Bai, Stefan Hinterstoisser, Sivlvio Savarese, and Mrinal Kalakrishnan · 2018
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