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Accurately simulating whether an object will be lifted securely or dropped during grasping is a longstanding Sim2Real challenge.
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Gilles Marckmann and Erwan Verron · 2006
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Jan Bender et al · 2014
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“Deep learning for detecting robotic grasps”
Ian Lenz, Honglak Lee and Ashutosh Saxena · 2015
Cited alongside, same era.
“Grasp quality measures: review and performance”
M“’aximo Roa and Ra“’ul Su“’arez · 2015
Cited alongside, same era.
“The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets”
Takaya Saito and Marc Rehmsmeier · 2015
Cited alongside, same era.
“Deep learning a grasp function for grasping under gripper pose uncertainty”
Edward Johns, Stefan Leutenegger and Andrew Davison · 2016
Cited alongside, same era.
“Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours”
Lerrel Pinto and Abhinav Gupta · 2016
“A billion ways to grasp: An evaluation of grasp sampling schemes on a dense, physics-based grasp data set”
Clemens Eppner, Arsalan Mousavian and Dieter Fox · 2019
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Miles Macklin et al · 2019
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“Learning ambidextrous robot grasping policies”
Jeffrey Mahler et al · 2019
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“ACRONYM: A Large-Scale Grasp Dataset Based on Simulation”
Clemens Eppner, Arsalan Mousavian and Dieter Fox · 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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“Incremental potential contact: Intersection-and inversion-free, large-deformation dynamics”
Minchen Li et al · 2020
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Cited alongside, same era.
“Stable simulation of underactuated compliant hands”
Alessio Rocchi, Barrett Ames, Zhi Li and Kris Hauser · 2016
Cited alongside, same era.
“Design of parallel-jaw gripper tip surfaces for robust grasping”
Menglong Guo et al · 2017
Cited alongside, same era.
“Learning deep policies for robot bin picking by simulating robust grasping sequences”
Jeffrey Mahler and Ken Goldberg · 2017
Cited alongside, same era.
“Grasping posture estimation for a two-finger parallel gripper with soft material jaws using a curved contact area friction model.”
Jingyi Xu, Nicolas Alt, Zhongyao Zhang and Eckehard Steinbach · 2017
Cited alongside, same era.
“Scalable deep reinforcement learning for vision-based robotic manipulation”
Dmitry Kalashnikov et al · 2018
Cited alongside, same era.
“GPU-accelerated robotic simulation for distributed reinforcement learning”
Jacky Liang et al · 2018
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Later among the works it cites.
“Learning robust, real-time, reactive robotic grasping”
Douglas Morrison, Peter Corke and J“”urgen Leitner · 2020
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“6DFC: Efficiently Planning Soft Non-Planar Area Contact Grasps using 6D Friction Cones”
Jingyi Xu, Michael Danielczuk, Eckehard Steinbach and Ken Goldberg · 2020
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“Towards Robotic Assembly by Predicting Robust, Precise and Task-oriented Grasps”
Jialiang Zhao, Daniel Troniak and Oliver Kroemer · 2020
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“Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger”
Arthur Allshire et al · 2021
Closest in time.
“PyBullet, a Python module for physics simulation for games, robotics and machine learning”, http://pybullet.org , 2016–2021
Erwin Coumans and Yunfei Bai · 2021
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“DefGraspSim: Simulation-based grasping of 3D deformable objects”
Isabella Huang et al · 2021
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“Medial IPC: accelerated incremental potential contact with medial elastics”
Lei Lan et al · 2021
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“Sim-to-real for robotic tactile sensing via physics-based simulation and learned latent projections”
Yashraj Narang et al · 2021
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“6DLS: Modeling Nonplanar Frictional Surface Contacts for Grasping Using 6-D Limit Surfaces”
Jingyi Xu, Tamay Aykut, Daolin Ma and Eckehard Steinbach · 2021
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