Robotic Continuous Grasping System by Shape Transformer-Guided Multiobject Category-Level 6-D Pose Estimation
J Liu, W Sun, C Liu, X Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Robotic grasping is one of the key functions for realizing industrial automation and human–
machine interaction. However, current robotic grasping methods for unknown objects mainly …
machine interaction. However, current robotic grasping methods for unknown objects mainly …
A depth adaptive feature extraction and dense prediction network for 6-D pose estimation in robotic grasping
Estimating the 6-D pose of an object is a vital and challenging task for robot vision systems
in industrial robotic grasping. With the wide use of 3-D cameras, the additional acquired …
in industrial robotic grasping. With the wide use of 3-D cameras, the additional acquired …
Domain-generalized robotic picking via contrastive learning-based 6-d pose estimation
J Liu, W Sun, H Yang, C Liu, X Zhang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Vision-guided robotic picking in 3-D space is a key technology for industrial automation and
intelligent manufacturing. However, existing methods rely on labeled real-world data for …
intelligent manufacturing. However, existing methods rely on labeled real-world data for …
[HTML][HTML] A comprehensive RGB-D dataset for 6D pose estimation for industrial robots pick and place: Creation and real-world validation
In the field of robotic grasping, 2D pose estimation algorithms are outdated and insufficient
for modern requirements. Transitioning to 6D pose estimation of objects offers, particularly …
for modern requirements. Transitioning to 6D pose estimation of objects offers, particularly …
Mitigating imbalances in heterogeneous feature fusion for multi-class 6D pose estimation
Most 6D pose studies often treat RGB and Depth features equally in fusion, potentially
limiting model generalization, especially in multi-class tasks. This limitation arises from …
limiting model generalization, especially in multi-class tasks. This limitation arises from …
Core sample consensus method for two-view correspondence matching
Exploring reliable correspondences in a given putative set is a fundamental task in two-view
geometry estimation. The random sample consensus (RANSAC) method is a widely used …
geometry estimation. The random sample consensus (RANSAC) method is a widely used …
Learning shared template representation with augmented feature for multi-object pose estimation
Q Luo, TB Xu, F Liu, T Li, Z Wei - Neural Networks, 2024 - Elsevier
Template matching pose estimation methods based on deep learning have made significant
advancements via metric learning or reconstruction learning. Existing approaches primarily …
advancements via metric learning or reconstruction learning. Existing approaches primarily …
PoseDiffusion: A Coarse-to-Fine Framework for Unseen Object 6-DoF Pose Estimation
J Zhou, Q Zhu, Y Wang, M Feng, C Wu… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Accurately estimating the six-degrees of freedom (DoF) pose of unseen objects is crucial for
successful robotic manipulation in industrial automation. Some existing methods for this task …
successful robotic manipulation in industrial automation. Some existing methods for this task …
SS-Pose: Self-Supervised 6-D Object Pose Representation Learning Without Rendering
Object pose estimation has extensive applications in various industrial scenarios. However,
the heavy reliance on dense 6-D annotation and textured object models has become a …
the heavy reliance on dense 6-D annotation and textured object models has become a …
Zero-Shot 3D Pose Estimation of Unseen Object by Two-step RGB-D Fusion
G Duan, S Cheng, Z Liu, Y Zheng, Y Su, J Tan - Neurocomputing, 2024 - Elsevier
Abstract 3D Object pose estimation is a critical task in many real-world applications, eg,
robotic manipulation and augmented reality. Most existing methods focus on estimating the …
robotic manipulation and augmented reality. Most existing methods focus on estimating the …