Experimental Comparison of Two 6D Pose Estimation Algorithms in Robotic Fruit-Picking Tasks
This paper presents an experimental comparison between two existing methods representative of two categories of 6D pose estimation algorithms nowadays commonly used in the robotics community. The first category includes purely deep learning methods, while the second one includes hybrid approaches co...
Saved in:
| Main Authors: | Alessio Benito Alterani, Marco Costanzo, Marco De Simone, Sara Federico, Ciro Natale |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-08-01
|
| Series: | Robotics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2218-6581/13/9/127 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Adaptive Grasp Pose Optimization for Robotic Arms Using Low-Cost Depth Sensors in Complex Environments
by: Aiguo Chen, et al.
Published: (2025-02-01) -
A Light-Weight Grasping Pose Estimation Method for Mobile Robotic Arms Based on Depthwise Separable Convolution
by: Jianguo Duan, et al.
Published: (2025-01-01) -
Cascaded Feature Fusion Grasping Network for Real-Time Robotic Systems
by: Hao Li, et al.
Published: (2024-12-01) -
Command-driven semantic robotic grasping towards user-specified tasks
by: Qing Lyu, et al.
Published: (2025-06-01) -
Gripping Success Metric for Robotic Fruit Harvesting
by: Dasom Seo, et al.
Published: (2024-12-01)