A Framework for Joint Grasp and Motion Planning in Confined Spaces
Author:
Affiliation:
1. Aston University,The Department of Applied AI & Robotics,Birmingham,UK
2. Czech Technical University Prague,The Faculty of Electrical Engineering,Prague,Czech Republic
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10604286/10604296/10604306.pdf?arnumber=10604306
Reference34 articles.
1. Dex-Net 1.0: A cloud-based network of 3D objects for robust grasp planning using a Multi-Armed Bandit model with correlated rewards
2. 6-DOF GraspNet: Variational Grasp Generation for Object Manipulation
3. End-to-End Learning to Grasp via Sampling From Object Point Clouds
4. GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping
5. Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenes
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