Scene Prediction and Manipulator Grasp Pose Estimation Based on YOLO-GraspNet
Author:
Affiliation:
1. Shanghai Donghai Vocational & Technical College,School of Mechanical and Electrical Engineering,Shanghai,China
2. Shanghai Dianji University,School of Mechanical Engineering,Shanghai,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10140173/10140194/10141255.pdf?arnumber=10141255
Reference20 articles.
1. Real-Time Monocular Pose Estimation of 3D Objects Using Temporally Consistent Local Color Histograms
2. SimTrack: A simulation-based framework for scalable real-time object pose detection and tracking
3. Learning Analysis-by-Synthesis for 6D Pose Estimation in RGB-D Images
4. Real-Time Seamless Single Shot 6D Object Pose Prediction
5. Pointnet++: Deep hierarchical feature learning on point sets in a metric space;qi,2017
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1. Lightweight-Shaped Object Grasping Detection Network Based on Feature Fusion;International Journal of Pattern Recognition and Artificial Intelligence;2024-09-04
2. Vision-based robotic grasping using faster R-CNN–GRCNN dual-layer detection mechanism;Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture;2024-05-17
3. Real-Time Object Detection and Robotic Manipulation for Agriculture Using a YOLO-Based Learning Approach;2024 IEEE International Conference on Industrial Technology (ICIT);2024-03-25
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