Challenges and opportunities on AR/VR technologies for manufacturing systems in the context of industry 4.0: A state of the art review
M Eswaran, MVAR Bahubalendruni - Journal of Manufacturing Systems, 2022 - Elsevier
Manufacturing industries are currently experiencing the fourth revolution with penetration of
new immersive technologies extremely focused on the flexible manufacturing and human …
new immersive technologies extremely focused on the flexible manufacturing and human …
Augmented reality-based guidance in product assembly and maintenance/repair perspective: A state of the art review on challenges and opportunities
Manufacturing industries are currently experiencing the fourth industrial revolution with the
rapid advancements in immersive technologies for human–machine interaction (HMI) and …
rapid advancements in immersive technologies for human–machine interaction (HMI) and …
Rotation-invariant transformer for point cloud matching
The intrinsic rotation invariance lies at the core of matching point clouds with handcrafted
descriptors. However, it is widely despised by recent deep matchers that obtain the rotation …
descriptors. However, it is widely despised by recent deep matchers that obtain the rotation …
Ssd-6d: Making rgb-based 3d detection and 6d pose estimation great again
We present a novel method for detecting 3D model instances and estimating their 6D poses
from RGB data in a single shot. To this end, we extend the popular SSD paradigm to cover …
from RGB data in a single shot. To this end, we extend the popular SSD paradigm to cover …
The perfect match: 3d point cloud matching with smoothed densities
We propose 3DSmoothNet, a full workflow to match 3D point clouds with a siamese deep
learning architecture and fully convolutional layers using a voxelized smoothed density …
learning architecture and fully convolutional layers using a voxelized smoothed density …
Ppfnet: Global context aware local features for robust 3d point matching
Abstract We present PPFNet-Point Pair Feature NETwork for deeply learning a globally
informed 3D local feature descriptor to find correspondences in unorganized point clouds …
informed 3D local feature descriptor to find correspondences in unorganized point clouds …
3D point capsule networks
In this paper, we propose 3D point-capsule networks, an auto-encoder designed to process
sparse 3D point clouds while preserving spatial arrangements of the input data. 3D capsule …
sparse 3D point clouds while preserving spatial arrangements of the input data. 3D capsule …
Ppf-foldnet: Unsupervised learning of rotation invariant 3d local descriptors
We present PPF-FoldNet for unsupervised learning of 3D local descriptors on pure point
cloud geometry. Based on the folding-based auto-encoding of well known point pair …
cloud geometry. Based on the folding-based auto-encoding of well known point pair …
Semantics for robotic mapping, perception and interaction: A survey
For robots to navigate and interact more richly with the world around them, they will likely
require a deeper understanding of the world in which they operate. In robotics and related …
require a deeper understanding of the world in which they operate. In robotics and related …
Learning multiview 3d point cloud registration
We present a novel, end-to-end learnable, multiview 3D point cloud registration algorithm.
Registration of multiple scans typically follows a two-stage pipeline: the initial pairwise …
Registration of multiple scans typically follows a two-stage pipeline: the initial pairwise …