Jeffrey Mahler

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研究焦点

主要成就

代表论文

1. 1
   Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics

   1,162 次引用 · 2017
2. 2
   Learning ambidextrous robot grasping policies

   578 次引用 · 2019
3. 3
   Dex-Net 1.0: A cloud-based network of 3D objects for robust grasp planning using a Multi-Armed Bandit model with correlated rewards

   374 次引用 · 2016
4. 4
   Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics

   277 次引用 · 2017
5. 5
   Segmenting Unknown 3D Objects from Real Depth Images using Mask R-CNN Trained on Synthetic Data

   189 次引用 · 2019
6. 6
   Learning Deep Policies for Robot Bin Picking by Simulating Robust Grasping Sequences

   145 次引用 · 2017
7. 7
   On-Policy Dataset Synthesis for Learning Robot Grasping Policies Using Fully Convolutional Deep Networks

   126 次引用 · 2019
8. 8
   Autonomous multilateral debridement with the Raven surgical robot

   121 次引用 · 2014
9. 9
   Learning accurate kinematic control of cable-driven surgical robots using data cleaning and Gaussian Process Regression

   76 次引用 · 2014
10. 10
    Linear Push Policies to Increase Grasp Access for Robot Bin Picking

    62 次引用 · 2018

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