Smart industrial robot control trends, challenges and opportunities within manufacturing
J Arents, M Greitans - Applied Sciences, 2022 - mdpi.com
Industrial robots and associated control methods are continuously developing. With the
recent progress in the field of artificial intelligence, new perspectives in industrial robot …
recent progress in the field of artificial intelligence, new perspectives in industrial robot …
Deep learning approaches to grasp synthesis: A review
Grasping is the process of picking up an object by applying forces and torques at a set of
contacts. Recent advances in deep learning methods have allowed rapid progress in robotic …
contacts. Recent advances in deep learning methods have allowed rapid progress in robotic …
Wonder3d: Single image to 3d using cross-domain diffusion
In this work we introduce Wonder3D a novel method for generating high-fidelity textured
meshes from single-view images with remarkable efficiency. Recent methods based on the …
meshes from single-view images with remarkable efficiency. Recent methods based on the …
Diffusion-sdf: Conditional generative modeling of signed distance functions
Probabilistic diffusion models have achieved state-of-the-art results for image synthesis,
inpainting, and text-to-image tasks. However, they are still in the early stages of generating …
inpainting, and text-to-image tasks. However, they are still in the early stages of generating …
[HTML][HTML] A review on reinforcement learning for contact-rich robotic manipulation tasks
Í Elguea-Aguinaco, A Serrano-Muñoz… - Robotics and Computer …, 2023 - Elsevier
Research and application of reinforcement learning in robotics for contact-rich manipulation
tasks have exploded in recent years. Its ability to cope with unstructured environments and …
tasks have exploded in recent years. Its ability to cope with unstructured environments and …
Dex-NeRF: Using a neural radiance field to grasp transparent objects
The ability to grasp and manipulate transparent objects is a major challenge for robots.
Existing depth cameras have difficulty detecting, localizing, and inferring the geometry of …
Existing depth cameras have difficulty detecting, localizing, and inferring the geometry of …
Learning high-DOF reaching-and-grasping via dynamic representation of gripper-object interaction
We approach the problem of high-DOF reaching-and-grasping via learning joint planning of
grasp and motion with deep reinforcement learning. To resolve the sample efficiency issue …
grasp and motion with deep reinforcement learning. To resolve the sample efficiency issue …
Nerf in the palm of your hand: Corrective augmentation for robotics via novel-view synthesis
Expert demonstrations are a rich source of supervision for training visual robotic
manipulation policies, but imitation learning methods often require either a large number of …
manipulation policies, but imitation learning methods often require either a large number of …
Rgb matters: Learning 7-dof grasp poses on monocular rgbd images
General object grasping is an important yet unsolved problem in the field of robotics. Most of
the current methods either generate grasp poses with few DoF that fail to cover most of the …
the current methods either generate grasp poses with few DoF that fail to cover most of the …
Deep learning on monocular object pose detection and tracking: A comprehensive overview
Object pose detection and tracking has recently attracted increasing attention due to its wide
applications in many areas, such as autonomous driving, robotics, and augmented reality …
applications in many areas, such as autonomous driving, robotics, and augmented reality …