Vision-based robotic gras** from object localization, object pose estimation to grasp estimation for parallel grippers: a review
This paper presents a comprehensive survey on vision-based robotic gras**. We
conclude three key tasks during vision-based robotic gras**, which are object localization …
conclude three key tasks during vision-based robotic gras**, which are object localization …
Data-driven robotic visual gras** detection for unknown objects: A problem-oriented review
H Tian, K Song, S Li, S Ma, J Xu, Y Yan - Expert Systems with Applications, 2023 - Elsevier
This paper presents a comprehensive survey of data-driven robotic visual gras**
detection (DRVGD) for unknown objects. We review both object-oriented and scene …
detection (DRVGD) for unknown objects. We review both object-oriented and scene …
Graspnet-1billion: A large-scale benchmark for general object gras**
Object gras** is critical for many applications, which is also a challenging computer vision
problem. However, for cluttered scene, current researches suffer from the problems of …
problem. However, for cluttered scene, current researches suffer from the problems of …
Acronym: A large-scale grasp dataset based on simulation
We introduce ACRONYM, a dataset for robot grasp planning based on physics simulation.
The dataset contains 17.7 M parallel-jaw grasps, spanning 8872 objects from 262 different …
The dataset contains 17.7 M parallel-jaw grasps, spanning 8872 objects from 262 different …
End-to-end trainable deep neural network for robotic grasp detection and semantic segmentation from rgb
In this work, we introduce a novel, end-to-end trainable CNN-based architecture to deliver
high quality results for grasp detection suitable for a parallel-plate gripper, and semantic …
high quality results for grasp detection suitable for a parallel-plate gripper, and semantic …
Improved multi-stream convolutional block attention module for sEMG-based gesture recognition
S Wang, L Huang, D Jiang, Y Sun, G Jiang… - … in Bioengineering and …, 2022 - frontiersin.org
As a key technology for the non-invasive human-machine interface that has received much
attention in the industry and academia, surface EMG (sEMG) signals display great potential …
attention in the industry and academia, surface EMG (sEMG) signals display great potential …
When transformer meets robotic gras**: Exploits context for efficient grasp detection
In this letter, we present a transformer-based architecture, namely TF-Grasp, for robotic
grasp detection. The developed TF-Grasp framework has two elaborate designs making it …
grasp detection. The developed TF-Grasp framework has two elaborate designs making it …
Gras** pose detection for loose stacked object based on convolutional neural network with multiple self-powered sensors information
J Yun, D Jiang, Y Sun, L Huang, B Tao… - IEEE Sensors …, 2022 - ieeexplore.ieee.org
There are a variety of objects, random postures and multiple objects stacked in a
disorganized manner in unstructured home applications, which leads to the object gras** …
disorganized manner in unstructured home applications, which leads to the object gras** …
Comprehensive review on reaching and gras** of objects in robotics
QM Marwan, SC Chua, LC Kwek - Robotica, 2021 - cambridge.org
Interaction between a robot and its environment requires perception about the environment,
which helps the robot in making a clear decision about the object type and its location. After …
which helps the robot in making a clear decision about the object type and its location. After …
A novel robotic grasp detection method based on region proposal networks
Grasp detection based on deep learning is an important method for robots to accurately
perceive unstructured environments. However, the deep learning method widely used in …
perceive unstructured environments. However, the deep learning method widely used in …