Modeling Grasp Motor Imagery through Deep Conditional Generative Models

11 January 2017

Papers citing "Modeling Grasp Motor Imagery through Deep Conditional Generative Models"

9 / 9 papers shown

Title
Planning Visual-Tactile Precision Grasps via Complementary Use of Vision and Touch Martin Matak Tucker Hermans 21 14 0 16 Dec 2022
Deep Learning Approaches to Grasp Synthesis: A Review Rhys Newbury Morris Gu Lachlan Chumbley Arsalan Mousavian Clemens Eppner ... A. Morales Tamim Asfour Danica Kragic D. Fox Akansel Cosgun 34 162 0 06 Jul 2022
Learning to Reorient Objects with Stable Placements Afforded by Extrinsic Supports Peng Xu Hu Cheng Jiankun Wang Max Q.-H. Meng 37 4 0 14 May 2022
DcnnGrasp: Towards Accurate Grasp Pattern Recognition with Adaptive Regularizer Learning Xiaoqin Zhang Ziwei Huang Jingjing Zheng Shuo Wang Xianta Jiang 11 2 0 11 May 2022
GKNet: grasp keypoint network for grasp candidates detection Ruinian Xu Fu-Jen Chu Patricio A. Vela 3DPC 24 37 0 16 Jun 2021
AdaGrasp: Learning an Adaptive Gripper-Aware Grasping Policy Zhenjia Xu Beichun Qi Shubham Agrawal Shuran Song 27 42 0 28 Nov 2020
Action Image Representation: Learning Scalable Deep Grasping Policies with Zero Real World Data Mohi Khansari Daniel Kappler Jianlan Luo Jeff Bingham Mrinal Kalakrishnan 22 25 0 13 May 2020
Learning better generative models for dexterous, single-view grasping of novel objects Marek Kopicki D. Belter J. Wyatt 16 32 0 13 Jul 2019
Planning Multi-Fingered Grasps as Probabilistic Inference in a Learned Deep Network Qingkai Lu Kautilya Chenna Balakumar Sundaralingam Tucker Hermans 22 88 0 10 Apr 2018