Point Cloud-Based Deep Learning in Industrial Production: A Survey
Y Liu, C Zhang, X Dong, J Ning - ACM Computing Surveys, 2025 - dl.acm.org
With the rapid development of 3D acquisition technology, point clouds have received
increasing attention. In recent years, point cloud-based deep learning has been applied to …
increasing attention. In recent years, point cloud-based deep learning has been applied to …
Development of robotic bin picking platform with cluttered objects using human guidance and convolutional neural network (CNN)
Industrial robots have been utilized for factory automation due to their high repeatability.
Along with the development of visual servo and machine learning techniques, various vision …
Along with the development of visual servo and machine learning techniques, various vision …
[HTML][HTML] Deep learning for 6D pose estimation of objects—A case study for autonomous driving
Nowadays, the potential benefits and implementation of autonomous driving have attracted
widespread attention from both industry and academia. This study will solve view-invariant …
widespread attention from both industry and academia. This study will solve view-invariant …
FPCC: Fast point cloud clustering-based instance segmentation for industrial bin-picking
Instance segmentation is an important pre-processing task in numerous real-world
applications, such as robotics, autonomous vehicles, and human–computer interaction …
applications, such as robotics, autonomous vehicles, and human–computer interaction …
Convolutional neural network-based visual servoing for eye-to-hand manipulator
We propose a CNN based visual servoing scheme for precise positioning of an eye-to-hand
manipulator in which the control input of a robot is calculated directly from images by a …
manipulator in which the control input of a robot is calculated directly from images by a …
3D object recognition and pose estimation from point cloud using stably observed point pair feature
D Li, H Wang, N Liu, X Wang, J Xu - IEEE Access, 2020 - ieeexplore.ieee.org
Recognition and pose estimation from 3D free-form objects is a key step for autonomous
robotic manipulation. Recently, the point pair features (PPF) voting approach has been …
robotic manipulation. Recently, the point pair features (PPF) voting approach has been …
A convolutional neural network for point cloud instance segmentation in cluttered scene trained by synthetic data without color
3D Instance segmentation is a fundamental task in computer vision. Effective segmentation
plays an important role in robotic tasks, augmented reality, autonomous driving, etc. With the …
plays an important role in robotic tasks, augmented reality, autonomous driving, etc. With the …
Hyperposepdf-hypernetworks predicting the probability distribution on so (3)
T Höfer, B Kiefer, M Messmer… - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
Pose estimation of objects in images is an essential problem in virtual and augmented
reality and robotics. Traditional solutions use depth cameras, which are expensive, and …
reality and robotics. Traditional solutions use depth cameras, which are expensive, and …
Fast object pose estimation using adaptive threshold for bin-picking
Robotic bin-picking is a common process in modern manufacturing, logistics, and
warehousing that aims to pick-up known or unknown objects with random poses out of a bin …
warehousing that aims to pick-up known or unknown objects with random poses out of a bin …
6D pose estimation of occlusion-free objects for robotic Bin-Picking using PPF-MEAM with 2D images (occlusion-free PPF-MEAM)
Pose estimation that locates objects in a bin is necessary for a robotic bin picking system.
Although many algorithms have shown high performance in pose estimation, most …
Although many algorithms have shown high performance in pose estimation, most …