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Imitation Learning (IL) is an effective framework to learn visuomotor skills from offline demonstration data.
“kPAM: KeyPoint Affordances for Category-Level Robotic Manipulation”, 2019
Lucas Manuelli, Wei Gao, Peter Florence and Russ Tedrake · 1903
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“A unified approach for motion and force control of robot manipulators: The operational space formulation”
Oussama Khatib · 1987
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“Alvinn: An autonomous land vehicle in a neural network”
Dean Pomerleau · 1989
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“A Framework for Behavioural Cloning.”
Michael Bain and Claude Sammut · 1995
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“Learning agents for uncertain environments”
Stuart Russell · 1998
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“Is imitation learning the route to humanoid robots?”
Stefan Schaal · 1999
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“Eye–hand coordination in object manipulation”
Roland Johansson, Göran Westling, Anders Bäckström and J Flanagan · 2001
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“Movement imitation with nonlinear dynamical systems in humanoid robots”
Auke Ijspeert, Jun Nakanishi and Stefan Schaal · 2002
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“Task and context determine where you look”
Constantin Rothkopf, Dana Ballard and Mary Hayhoe · 2007
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“Robot Programming by Demonstration”
Aude Billard, Sylvain Calinon, Rüdiger Dillmann and Stefan Schaal · 2008
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“Eye–hand coordination in a sequential target contact task”
Miles Bowman, Roland Johannson and John Flanagan · 2009
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“Automatic selection of task spaces for imitation learning”
Manuel Mühlig, Michael Gienger, Jochen Steil and Christian Goerick · 2009
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“Learning and Reproduction of Gestures by Imitation”
Sylvain Calinon et al · 2010
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“A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning”
Stéphane Ross, Geoffrey. Gordon and J. Bagnell · 2010
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“Mujoco: A physics engine for model-based control”
Emanuel Todorov, Tom Erez and Yuval Tassa · 2012
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“Recurrent models of visual attention”
Volodymyr Mnih, Nicolas Heess and Alex Graves · 2014
Cited alongside, same era.
“Deep spatial autoencoders for visuomotor learning”
Chelsea Finn et al · 2016
Cited alongside, same era.
“End-to-End Training of Deep Visuomotor Policies”, 2016
Sergey Levine, Chelsea Finn, Trevor Darrell and Pieter Abbeel · 2016
Cited alongside, same era.
“Faster r-cnn: Towards real-time object detection with region proposal networks”
Shaoqing Ren, Kaiming He, Ross Girshick and Jian Sun · 2016
Cited alongside, same era.
“One-Shot Visual Imitation Learning via Meta-Learning”
Chelsea Finn et al · 2017
Cited alongside, same era.
“Reinforcement learning with attention that works: A self-supervised approach”
Anthony Manchin, Ehsan Abbasnejad and Anton van Hengel · 2019
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Ajay Mandlekar et al · 2019
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“Towards interpretable reinforcement learning using attention augmented agents”
Alexander Mott et al · 2019
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“Learning to Generalize Across Long-Horizon Tasks from Human Demonstrations”
Ajay Mandlekar et al · 2020
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“Keypoints into the Future: Self-Supervised Correspondence in Model-Based Reinforcement Learning”
Lucas Manuelli, Yunzhu Li, Pete Florence and Russ Tedrake · 2020
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Michael Laskey et al · 2017
Cited alongside, same era.
“Learning manipulation skills from a single demonstration”
Peter Englert and Marc Toussaint · 2018
Cited alongside, same era.
“Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation”
Peter Florence, Lucas Manuelli and Russ Tedrake · 2018
Cited alongside, same era.
“Roboturk: A crowdsourcing platform for robotic skill learning through imitation”
Ajay Mandlekar et al · 2018
Cited alongside, same era.
“Learning synergies between pushing and grasping with self-supervised deep reinforcement learning”
Andy Zeng et al · 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 et al · 2018
Cited alongside, same era.
“Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation”
T. Zhang et al · 2018
Cited alongside, same era.
Later among the works it cites.
“Keto: Learning keypoint representations for tool manipulation”
Zengyi Qin et al · 2020
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“Learning to Compose Hierarchical Object-Centric Controllers for Robotic Manipulation”
Mohit Sharma et al · 2020
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“Grasping in the wild: Learning 6dof closed-loop grasping from low-cost demonstrations”
Shuran Song, Andy Zeng, Johnny Lee and Thomas Funkhouser · 2020
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“Neuroevolution of Self-Interpretable Agents” https://attentionagent.github.io
Yujin Tang, Duong Nguyen and David Ha · 2020
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“Spatial Action Maps for Mobile Manipulation”
Jimmy Wu et al · 2020
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“Form2fit: Learning shape priors for generalizable assembly from disassembly”
Kevin Zakka, Andy Zeng, Johnny Lee and Shuran Song · 2020
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“Tossingbot: Learning to throw arbitrary objects with residual physics”
Andy Zeng et al · 2020
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“robosuite: A Modular Simulation Framework and Benchmark for Robot Learning”
Yuke Zhu, Josiah Wong, Ajay Mandlekar and Roberto Martín-Martín · 2020
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“Show, attend and tell: Neural image caption generation with visual attention”
Kelvin Xu et al · 2057
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