Context-Aware Grasp Generation in Cluttered Scenes
Author:
Affiliation:
1. FPT University,ICT Department,Hanoi,Vietnam
2. Orebro University,Centre for Applied Autonomous Sensor Systems (AASS),Sweden
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9811522/9811357/09811371.pdf?arnumber=9811371
Reference41 articles.
1. Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach
2. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
3. SSD-6D: Making RGB-Based 3D Detection and 6D Pose Estimation Great Again
4. PVNet: Pixel-Wise Voting Network for 6DoF Pose Estimation
5. Attentional PointNet for 3D-Object Detection in Point Clouds
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3. Self-supervised Learning for Joint Pushing and Grasping Policies in Highly Cluttered Environments;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13
4. Graspability-Aware Object Pose Estimation in Cluttered Scenes;IEEE Robotics and Automation Letters;2024-04
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