Deep Learning Reactive Robotic Grasping With a Versatile Vacuum Gripper
Author:
Affiliation:
1. ACRO Research Group, Department of Mechanical Engineering, Diepenbeek, Belgium
2. LCE Research Group, Department of Mechanical Engineering, Heverlee, Belgium
Funder
China Scholarship Council
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/8860/10092518/09994578.pdf?arnumber=9994578
Reference60 articles.
1. Jacquard: A Large Scale Dataset for Robotic Grasp Detection
2. Dex-Net 3.0: Computing Robust Vacuum Suction Grasp Targets in Point Clouds Using a New Analytic Model and Deep Learning
3. Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics
4. Towards MRI-Based Autonomous Robotic US Acquisitions: A First Feasibility Study
5. Grasp planning for everyday objects based on primitive shape representation for parallel jaw grippers
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