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Modeling Grasp Type Improves Learning-Based Grasp Planning

Modeling Grasp Type Improves Learning-Based Grasp Planning

10 January 2019
Qingkai Lu
Tucker Hermans
ArXiv (abs)PDFHTML

Papers citing "Modeling Grasp Type Improves Learning-Based Grasp Planning"

20 / 20 papers shown
Title
First Plan Then Evaluate: Use a Vectorized Motion Planner for Grasping
First Plan Then Evaluate: Use a Vectorized Motion Planner for Grasping
Martin Matak
Mohanraj Devendran Ashanti
Karl Van Wyk
Tucker Hermans
120
1
0
08 Sep 2025
23 DoF Grasping Policies from a Raw Point Cloud
23 DoF Grasping Policies from a Raw Point Cloud
Martin Matak
Karl Van Wyk
Tucker Hermans
3DPC
263
1
0
21 Nov 2024
Planning Visual-Tactile Precision Grasps via Complementary Use of Vision
  and Touch
Planning Visual-Tactile Precision Grasps via Complementary Use of Vision and TouchIEEE Robotics and Automation Letters (RA-L), 2022
Martin Matak
Tucker Hermans
166
22
0
16 Dec 2022
Where To Start? Transferring Simple Skills to Complex Environments
Where To Start? Transferring Simple Skills to Complex EnvironmentsConference on Robot Learning (CoRL), 2022
Vitalis Vosylius
Edward Johns
211
13
0
12 Dec 2022
Generating Task-specific Robotic Grasps
Generating Task-specific Robotic Grasps
Mark Robson
Mohan Sridharan
90
1
0
20 Mar 2022
Simulation-based Bayesian inference for multi-fingered robotic grasping
Simulation-based Bayesian inference for multi-fingered robotic grasping
Norman Marlier
O. Bruls
Gilles Louppe
199
6
0
29 Sep 2021
Learn to Grasp with Less Supervision: A Data-Efficient Maximum
  Likelihood Grasp Sampling Loss
Learn to Grasp with Less Supervision: A Data-Efficient Maximum Likelihood Grasp Sampling LossIEEE International Conference on Robotics and Automation (ICRA), 2021
Xinghao Zhu
Yefan Zhou
Yongxiang Fan
Lingfeng Sun
Jianyu Chen
Masayoshi Tomizuka
211
15
0
10 Aug 2021
The Grasps Under Varied Object Orientation Dataset: Relation Between
  Grasps and Object Orientation
The Grasps Under Varied Object Orientation Dataset: Relation Between Grasps and Object Orientation
Chang Cheng
Yadong Yan
Mingjun Guan
Jianan Zhang
Yu Wang
129
1
0
27 Jun 2021
Learning to Detect Multi-Modal Grasps for Dexterous Grasping in Dense
  Clutter
Learning to Detect Multi-Modal Grasps for Dexterous Grasping in Dense ClutterIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2021
Matt Corsaro
Stefanie Tellex
George Konidaris
3DPC
175
12
0
07 Jun 2021
Volumetric Grasping Network: Real-time 6 DOF Grasp Detection in Clutter
Volumetric Grasping Network: Real-time 6 DOF Grasp Detection in ClutterConference on Robot Learning (CoRL), 2021
Michel Breyer
Jen Jen Chung
Lionel Ott
Roland Siegwart
Juan I. Nieto
3DPC
210
205
0
04 Jan 2021
Comparing Piezoresistive Substrates for Tactile Sensing in Dexterous
  Hands
Comparing Piezoresistive Substrates for Tactile Sensing in Dexterous Hands
R. Miles
Martin Matak
Sarah Hood
M. Shanthi
D. Young
Tucker Hermans
248
2
0
11 Nov 2020
Generalized Grasping for Mechanical Grippers for Unknown Objects with
  Partial Point Cloud Representations
Generalized Grasping for Mechanical Grippers for Unknown Objects with Partial Point Cloud Representations
M. Hegedus
Kamal Gupta
M. Mehrandezh
3DPC
125
0
0
23 Jun 2020
Multi-Fingered Active Grasp Learning
Multi-Fingered Active Grasp Learning
Qingkai Lu
Mark Van der Merwe
Tucker Hermans
195
37
0
06 Jun 2020
Contextual Reinforcement Learning of Visuo-tactile Multi-fingered
  Grasping Policies
Contextual Reinforcement Learning of Visuo-tactile Multi-fingered Grasping Policies
Visak C. V. Kumar
Tucker Hermans
Dieter Fox
Stan Birchfield
Jonathan Tremblay
252
16
0
21 Nov 2019
Learning Continuous 3D Reconstructions for Geometrically Aware Grasping
Learning Continuous 3D Reconstructions for Geometrically Aware GraspingIEEE International Conference on Robotics and Automation (ICRA), 2019
Mark Van der Merwe
Qingkai Lu
Balakumar Sundaralingam
Martin Matak
Tucker Hermans
3DV
235
98
0
02 Oct 2019
MAT: Multi-Fingered Adaptive Tactile Grasping via Deep Reinforcement
  Learning
MAT: Multi-Fingered Adaptive Tactile Grasping via Deep Reinforcement LearningConference on Robot Learning (CoRL), 2019
Bohan Wu
Iretiayo Akinola
Jacob Varley
Peter K. Allen
167
55
0
10 Sep 2019
Learning better generative models for dexterous, single-view grasping of
  novel objects
Learning better generative models for dexterous, single-view grasping of novel objects
Marek Kopicki
D. Belter
J. Wyatt
166
34
0
13 Jul 2019
A Review of Robot Learning for Manipulation: Challenges,
  Representations, and Algorithms
A Review of Robot Learning for Manipulation: Challenges, Representations, and AlgorithmsJournal of machine learning research (JMLR), 2019
Oliver Kroemer
S. Niekum
George Konidaris
331
439
0
06 Jul 2019
State Classification of Cooking Objects Using a VGG CNN
State Classification of Cooking Objects Using a VGG CNN
Kyle Mott
88
4
0
21 Apr 2019
Generating Grasp Poses for a High-DOF Gripper Using Neural Networks
Generating Grasp Poses for a High-DOF Gripper Using Neural NetworksIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2019
Min Liu
Zherong Pan
Kai Xu
Kanishka Ganguly
Tianyi Zhou
347
79
0
01 Mar 2019
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